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MLSysBook Tools\n\n`binder/tools` contains production tooling for the MLSysBook source tree. These\ntools are part of how the book is built, checked, generated, audited, and\nreleased. Some are called by humans, some by CI, some by Binder commands, and\nsome by Quarto-adjacent generation workflows.\n\nDo not delete, rename, or move anything under this tree only because it looks\nlike a one-off script. First audit actual use in QMD files, Binder commands, CI,\nrelease scripts, documentation, and generated-asset workflows.\n\n## Production Policy\n\n- Treat `binder/tools` as book infrastructure, not scratch space.\n- Before relocating or removing a tool, search for call sites with `rg`, update\n  callers and documentation, and run the relevant validation command.\n- Prefer stable modules or Binder-facing entrypoints for new book dependencies.\n  Scripts may remain as compatibility entrypoints when they are already part of\n  production workflows.\n- Generated assets should record their source tool in the nearby README or\n  comments so future editors can regenerate rather than hand-edit them.\n- Tooling that depends on external packages should document the runtime command\n  and any special environment setup.\n\n## Current Areas\n\n| Area | Purpose |\n|---|---|\n| `scripts/` | Python and shell entrypoints for generation, maintenance, release, and Quarto-adjacent workflows. |\n| `audit/` | Durable audit records and audit helpers used to track book quality work. |\n| `dependencies/` | Dependency and environment documentation. |\n| `git-hooks/` | Repository hook documentation and related setup. |\n\n## Figure Tool Ownership\n\nThe matplotlib figure style (palette, font stack, font sizes, figure size, and\nthe `setup_plot()` helper) has one source: `mlsysim/mlsysim/viz/style.py`,\nalongside the simulator-aware plotters in `mlsysim.viz`. Every figure, whether\na chapter cell or an `mlsysim` plotter, inherits the same sizes from it.\n\n```text\nmlsysim/mlsysim/viz/\n  style.py        # COLORS, set_book_style(), setup_plot(), BODY_FIGSIZE, MIN_FONT_PT\n  fonts/          # bundled TeX Gyre Heros faces registered by set_book_style()\nbinder/tools/figures/\n  style.py        # re-export of mlsysim.viz.style (the import path chapter cells use)\n```\n\nChapter cells may import either `binder.tools.figures.style` or `mlsysim.viz`;\nboth resolve to the same objects. Define nothing style-related in binder.\n\n`./binder/binder check figures --scope print-scale --volN` renders every\nmatplotlib body figure and checks it against the limits in `viz/style.py`\n(print scale, minimum font size, figures created without the style).\n","binder/tools/bib_lint_baseline.json":"{\n  \"description\": \"bib_lint allow-list: pre-existing violations grandfathered at the time of the baseline. New violations NOT in this file will block commits. Regenerate via: python3 binder/tools/bib_lint.py --all --baseline\",\n  \"generated\": \"2026-04-08\",\n  \"allowed\": [\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"ahn2022saycan\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"alshiekh2018safe\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"amanatides1987fast\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"ames2014control\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"annpureddy2011staliro\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"assran2023self\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"banerjee2018hands\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"barfoot2017state\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@article missing required field `journal`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"bishop1998methodology\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"brohan2023rt1\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"chen2018tvm\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"cheng2019end\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"codevilla2018offline\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"curless1996volumetric\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"dasari2019robonet\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"dreossi2019verifai\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"driess2023palme\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"florence2022implicit\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"foote2013tf\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"fremont2019scenic\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"furgale2013unified\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"gu2022open\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      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\"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/backmatter/appendix_assumptions.qmd\",\n    \"line\": 342,\n    \"message\": \"Closed name recovery_checkpoint_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/backmatter/appendix_assumptions.qmd\",\n    \"line\": 343,\n    \"message\": \"Closed name recovery_time_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/backmatter/appendix_assumptions.qmd\",\n    \"line\": 467,\n    \"message\": \"Closed name tenk_h100_it_mw_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/backmatter/appendix_assumptions.qmd\",\n    \"line\": 468,\n    \"message\": \"Closed name pue_extra_overhead_mw_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/backmatter/appendix_fleet.qmd\",\n    \"line\": 412,\n    \"message\": \"Closed name write_70b_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/backmatter/appendix_fleet.qmd\",\n    \"line\": 413,\n    \"message\": \"Closed name write_175b_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/backmatter/appendix_inference.qmd\",\n    \"line\": 287,\n    \"message\": \"Closed name expected_total_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/backmatter/appendix_reliability.qmd\",\n    \"line\": 559,\n    \"message\": \"Closed name _ckpt_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/compute_infrastructure/compute_infrastructure.qmd\",\n    \"line\": 1467,\n    \"message\": \"Closed name inf_weight_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/compute_infrastructure/compute_infrastructure.qmd\",\n    \"line\": 2690,\n    \"message\": \"Closed name weights_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/compute_infrastructure/compute_infrastructure.qmd\",\n    \"line\": 2691,\n    \"message\": \"Closed name gradients_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/compute_infrastructure/compute_infrastructure.qmd\",\n    \"line\": 2692,\n    \"message\": \"Closed name optimizer_m_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/compute_infrastructure/compute_infrastructure.qmd\",\n    \"line\": 2693,\n    \"message\": \"Closed name optimizer_v_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/compute_infrastructure/compute_infrastructure.qmd\",\n    \"line\": 3122,\n    \"message\": \"Closed name comm_phase_w_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/compute_infrastructure/compute_infrastructure.qmd\",\n    \"line\": 3123,\n    \"message\": \"Closed name power_delta_w_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/compute_infrastructure/compute_infrastructure.qmd\",\n    \"line\": 3775,\n    \"message\": \"Closed name mtbf_system_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/distributed_training/distributed_training.qmd\",\n    \"line\": 983,\n    \"message\": \"Closed name exposed_step_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/distributed_training/distributed_training.qmd\",\n    \"line\": 985,\n    \"message\": \"Closed name t_compute_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/edge_intelligence/edge_intelligence.qmd\",\n    \"line\": 1062,\n    \"message\": \"Closed name battery_power_w_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/fault_tolerance/fault_tolerance.qmd\",\n    \"line\": 1900,\n    \"message\": \"Closed name training_step_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/fault_tolerance/fault_tolerance.qmd\",\n    \"line\": 2111,\n    \"message\": \"Closed name gpt3_shard_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/fault_tolerance/fault_tolerance.qmd\",\n    \"line\": 2304,\n    \"message\": \"Closed name t_write_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/fault_tolerance/fault_tolerance.qmd\",\n    \"line\": 2306,\n    \"message\": \"Closed name mtbf_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/fault_tolerance/fault_tolerance.qmd\",\n    \"line\": 2307,\n    \"message\": \"Closed name tau_opt_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/fault_tolerance/fault_tolerance.qmd\",\n    \"line\": 2586,\n    \"message\": \"Closed name min_write_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/fault_tolerance/fault_tolerance.qmd\",\n    \"line\": 2591,\n    \"message\": \"Closed name gpu_cpu_parallel_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/fault_tolerance/fault_tolerance.qmd\",\n    \"line\": 2592,\n    \"message\": \"Closed name gpu_cpu_single_path_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/fault_tolerance/fault_tolerance.qmd\",\n    \"line\": 2884,\n    \"message\": \"Closed name t_detect_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/inference/inference.qmd\",\n    \"line\": 2453,\n    \"message\": \"Closed name kv_savings_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/inference/inference.qmd\",\n    \"line\": 3775,\n    \"message\": \"Closed name nvlink_ms_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/inference/inference.qmd\",\n    \"line\": 3776,\n    \"message\": \"Closed name ib_ms_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/inference/inference.qmd\",\n    \"line\": 3777,\n    \"message\": \"Closed name eth_ms_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/introduction/introduction.qmd\",\n    \"line\": 1695,\n    \"message\": \"Closed name sync_energy_j_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/introduction/introduction.qmd\",\n    \"line\": 1697,\n    \"message\": \"Closed name sync_energy_mj_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/ops_scale/ops_scale.qmd\",\n    \"line\": 3143,\n    \"message\": \"Closed name mtbf_system_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/performance_engineering/performance_engineering.qmd\",\n    \"line\": 704,\n    \"message\": \"Closed name weight_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/performance_engineering/performance_engineering.qmd\",\n    \"line\": 706,\n    \"message\": \"Closed name decode_ms_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/security_privacy/security_privacy.qmd\",\n    \"line\": 1455,\n    \"message\": \"Closed name alert_interquery_ms_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 271,\n    \"message\": \"Closed name energy_kwh_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 927,\n    \"message\": \"Closed name operational_tonnes_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 929,\n    \"message\": \"Closed name embodied_tonnes_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 930,\n    \"message\": \"Closed name total_tonnes_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 1647,\n    \"message\": \"Closed name grid_ci_g_per_kwh_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 1659,\n    \"message\": \"Closed name embodied_daily_kg_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 1660,\n    \"message\": \"Closed name embodied_training_kg_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 1838,\n    \"message\": \"Closed name embodied_daily_kg_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 3203,\n    \"message\": \"Closed name phone_battery_j_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 3205,\n    \"message\": \"Closed name budget_j_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  }\n]","tinytorch/tools/README.md":"# Development Tools\n\nThis directory contains tools for TinyTorch maintainers and contributors.\n\n## Structure\n\n- **`release_check.py`** - The pre-release gate suite. `--fast` runs the 34 quick\n  gates; the full run adds the top-to-bottom notebook journey and the pytest\n  suite. `--list` prints every gate. See `RELEASE_TESTING.md`.\n- **`check_reference.py`** - Builds the instructor solutions into a temporary\n  package and runs the numerical and training regressions against it, so a stale\n  local export cannot make the check pass.\n- **`validate_nbgrader_config.py`** - Checks the nbgrader cell-header shapes and\n  `grade_id`s across all 20 modules. Expect `Passed: 20, Failed: 0`.\n- **`check_prose_solution_leaks.py`** - Fails if a graded solution is reprinted in\n  prose outside its `BEGIN/END SOLUTION` region.\n- **`check_grading_holes.py`** - Reports graded cells that pass on an empty student\n  notebook, which happens when a cell's assertions only reach regions tagged\n  `role=\"scaffold\"` and therefore shipped pre-solved.\n- **`dev/`** - Development environment setup and utilities.\n\n## For Students\n\nStudents don't need anything in this directory. Use the main setup scripts in the\nproject root.\n\n## For Developers\n\n- `RELEASE_TESTING.md` in this directory describes what each gate covers and what\n  it deliberately does not.\n- `../MODULE_ANATOMY.md` is the specification for how a module is built, and wins\n  whenever a module, a checklist, or an agent prompt disagrees with it.\n- `../CONTRIBUTING.md` covers the branch and release workflow.\n","staffml/ARCHITECTURE.md":"# StaffML Software Architecture\n\n> **High-Level System Architecture & Design Blueprint**\n> **Repository:** `MLSysBook` (`staffml/`)\n> **Platform:** [StaffML (https://mlsysbook.ai/staffml/)](https://mlsysbook.ai/staffml/)\n> **Audience:** Engineers, contributors, and systems researchers inspecting or extending the platform.\n\n---\n\n## 1. System Overview & Philosophy\n\n**StaffML** is an open-source, physics-grounded preparation and evaluation platform for machine learning systems engineers. Unlike conventional software engineering interview prep (which centers on algorithmic complexity and data structures), ML systems interviews require reasoning about physical hardware constraints: memory bandwidth limits, compute rooflines, interconnect bisections, numerical precision, and thermal/power budgets.\n\nThe central design principle of StaffML is:\n> *You can generate the code, but you cannot prompt your way out of a silicon bottleneck.*\n\n```mermaid\ngraph TD\n    subgraph \"1. Source of Truth (Git)\"\n        YAML[\"10,711 Structured YAMLs<br/>staffml/vault/questions/\"]\n        CHAINS[\"843 Socratic Chains<br/>staffml/vault/chains.json\"]\n        TAXONOMY[\"87 Topics & 13 Areas<br/>staffml/vault/taxonomy.yaml\"]\n        REGISTRY[\"Append-Only ID Registry<br/>staffml/vault/id-registry.yaml\"]\n    end\n\n    subgraph \"2. Compiler & Verification Engine\"\n        CLI[\"vault-cli (Python / Typer / Pydantic)\"]\n        CHECK[\"vault check (Fast, Structural & Slow Invariants)\"]\n        BUILD[\"vault build (Parallel Compiler)\"]\n        DB[\"SQLite Database (vault.db)\"]\n        STATIC[\"Static Corpus JSON (corpus.json)\"]\n    end\n\n    subgraph \"3. Serving & Edge Infrastructure\"\n        WORKER[\"Cloudflare Edge Worker (D1 + KV + Vector)\"]\n        LLM_RELAY[\"Multi-Provider LLM Adapter<br/>Groq ➔ OpenAI ➔ Anthropic ➔ Gemini\"]\n    end\n\n    subgraph \"4. Client Application (Next.js 16)\"\n        APP[\"Next.js App Router (16 Routes)\"]\n        PRACTICE[\"Spaced Repetition Practice\"]\n        ROOFLINE[\"Interactive Roofline Engine\"]\n        SIMULATOR[\"3D Parallelism Simulator\"]\n        GAUNTLET[\"Timed Gauntlet Mock Mode\"]\n        CONDUCTOR[\"Live Socratic AI Conductor\"]\n        EXPLORER[\"Radial Sunburst Explorer\"]\n    end\n\n    YAML --> CHECK\n    CHAINS --> CHECK\n    TAXONOMY --> CHECK\n    REGISTRY --> CHECK\n    CHECK --> BUILD\n    BUILD --> DB\n    BUILD --> STATIC\n    DB --> WORKER\n    STATIC --> APP\n    WORKER --> APP\n    APP --> PRACTICE\n    APP --> ROOFLINE\n    APP --> SIMULATOR\n    APP --> GAUNTLET\n    APP --> EXPLORER\n    APP --> CONDUCTOR\n    CONDUCTOR --> LLM_RELAY\n```\n\nThe system is decoupled into four modular pillars:\n1. **The Question Vault**: A human-first, git-tracked corpus of 10,711 validated YAML files conforming to LinkML/Pydantic schemas.\n2. **The Build & Tooling Layer (`vault-cli`)**: A high-performance compiler that validates invariants, tracks content hashes, and compiles SQLite (`vault.db`) and static bundles.\n3. **The Web Application (`app/`)**: A Next.js 16 App Router application supporting dual runtime modes (local static fallback vs edge-connected D1).\n4. **The Edge & LLM Conductor (`vault-worker` & `app/worker`)**: A Cloudflare Edge Worker providing low-latency Socratic mock interviewing via a resilient multi-provider fallback cascade.\n\n---\n\n## 2. Pillar 1: The Question Vault & Data Model\n\n### 2.1 Four-Axis Classification Schema\n\nEvery question in the vault is classified along four orthogonal axes enforced by LinkML schema v1.0 and Pydantic models:\n\n```mermaid\nclassDiagram\n    class Question {\n        +String schema_version\n        +String id\n        +Track track\n        +Level level\n        +Zone zone\n        +String topic\n        +String competency_area\n        +String bloom_level\n        +String title\n        +String scenario\n        +String question\n        +Visual visual\n        +Details details\n        +String status\n        +String provenance\n        +List~ChainRef~ chains\n    }\n\n    class Details {\n        +String realistic_solution\n        +String common_mistake\n        +String napkin_math\n        +List~String~ options\n        +Int correct_index\n        +List~Resource~ resources\n    }\n\n    class Visual {\n        +String kind\n        +String path\n        +String alt\n        +String caption\n    }\n\n    class ChainRef {\n        +String id\n        +Int position\n    }\n\n    Question *-- Details\n    Question o-- Visual\n    Question o-- ChainRef\n```\n\n- **Track (`track`)**: Deployment domain — `cloud`, `edge`, `mobile`, `tinyml`, or `global`.\n- **Level (`level`)**: Bloom's Taxonomy depth — `L1` (Recall), `L2` (Understand), `L3` (Apply), `L4` (Analyze), `L5` (Evaluate), `L6+` (Create/Architect).\n- **Zone (`zone`)**: 11 Ikigai problem zones — `recall`, `fluency`, `implement`, `analyze`, `diagnosis`, `specification`, `evaluation`, `mastery`, `optimization`, `design`, `realization`.\n- **Competency Area (`competency_area`)**: 13 technical disciplines — `architecture`, `compute`, `memory`, `networking`, `optimization`, `deployment`, `latency`, `power`, `precision`, `reliability`, `data`, `parallelism`, `cross-cutting`.\n\n### 2.2 Socratic Chains\n\nQuestions do not exist in isolation; they are linked into **Socratic Chains** (`staffml/vault/chains.json`). A chain represents a pedagogical progression through an ML systems problem:\n1. **Entry Point (L1/L2)**: Establishes baseline facts (e.g. GPU memory bandwidth or FlashAttention tile size).\n2. **Application & Math (L3)**: Requires arithmetic derivation (e.g. arithmetic intensity or KV cache sizing).\n3. **System Breakdown & Analysis (L4/L5)**: Diagnoses bottlenecks under scale (e.g. pipeline bubbles, NCCL ring contention, thermal throttling).\n4. **Architecture & Synthesis (L6+)**: Evaluates holistic trade-offs under competing constraints.\n\nChains support two progression tiers:\n- **Primary Tier**: Strict Bloom monotonic progression ($\\Delta \\in \\{1, 2\\}$).\n- **Secondary Tier**: Lenient coverage sweeps ($\\Delta \\in \\{0, 1, 2, 3\\}$).\n\n### 2.3 Cryptographic Integrity & Merkle Release Hashes\n\nEvery question receives a deterministic `content_hash` (SHA-256 over normalized canonical JSON of semantic fields). Releases compute a **Merkle root** (`release_hash`) over all published question hashes, taxonomy, chains, zones, and release policy. This provides cryptographic verification for academic citation and drift detection across deployments.\n\n---\n\n## 3. Pillar 2: The CLI & Compiler (`vault-cli`)\n\n`vault-cli` is a typed Python package built with Typer and Rich.\n\n```\nvault-cli/\n├── src/vault_cli/\n│   ├── main.py             # CLI entry point\n│   ├── loader.py           # Parallel YAML filesystem loader + sidecar chain joiner\n│   ├── validator.py        # Multi-tier invariant validation\n│   ├── compiler.py         # SQLite / D1 compiler (compiles vault.db)\n│   ├── models.py           # Pydantic schema models\n│   ├── hashing.py          # Deterministic SHA-256 & Merkle tree calculation\n│   ├── legacy_export.py    # Generates public/data/corpus.json\n│   └── commands/           # check, doctor, build, publish, ship, new, promote\n└── tests/                  # Pytest test suite (97 tests)\n```\n\n### 3.1 Invariant Validation Tiers\n\n`vault check` executes three validation tiers:\n- **Fast Tier (<1s)**: Schema validation, unique ID registry check, path lowercase conventions, required fields.\n- **Structural Tier (<10s)**: Cross-references between taxonomy, topics, chains, 3-part `common_mistake` markers (`**The Pitfall:**`, `**The Rationale:**`, `**The Consequence:**`), `napkin_math` structure, and visual asset existence.\n- **Slow Tier**: Link-rot checks across external documentation URLs and LLM math verification.\n\n---\n\n## 4. Pillar 3: Web Application Architecture (`app/`)\n\nThe frontend is built with **Next.js 16 (App Router)**, TypeScript, Tailwind CSS, KaTeX, and Framer Motion.\n\n```mermaid\ngraph LR\n    subgraph \"Data Access Layer (lib/corpus.ts)\"\n        CONFIG{\"vault-config.ts<br/>(static vs worker)\"}\n        LOCAL[\"Fetch /data/corpus.json<br/>(Static Bundle)\"]\n        REMOTE[\"Fetch Cloudflare Worker API<br/>(D1 Queries)\"]\n        CONFIG -->|Static Mode| LOCAL\n        CONFIG -->|Worker Mode| REMOTE\n    end\n\n    subgraph \"Interactive Modules\"\n        SR[\"Spaced Repetition<br/>(lib/progress.ts)\"]\n        ROOF[\"Roofline Engine<br/>(lib/hardware.ts)\"]\n        SIM[\"3D Sim Engine<br/>(lib/simulator.ts)\"]\n        COND[\"AI Conductor<br/>(lib/interview-conductor.ts)\"]\n    end\n\n    LOCAL --> SR\n    REMOTE --> SR\n    SR --> ROOF\n    SR --> SIM\n    SR --> COND\n```\n\n### 4.1 Dual-Mode Runtime Architecture\n\nThe web application supports two runtime modes via `src/lib/vault-config.ts`:\n1. **Worker Mode (`worker`)**: Light initial page load. Fetches catalog metadata initially and retrieves heavy fields (`scenario`, `details.*`) lazily from the Cloudflare Worker API.\n2. **Static Mode (`static`)**: Fully offline-capable and zero-dependency. Bundles the compiled `corpus.json` in `public/data/` for standalone local deployment or static hosting.\n\n### 4.2 Spaced Repetition Engine (`lib/progress.ts`)\n\nStaffML implements an adapted SuperMemo SM-2 spaced repetition algorithm stored locally in browser `localStorage`:\n- **Interval Progression**: Successful recalls advance review intervals (1 day $\\rightarrow$ 3 days $\\rightarrow$ 7 days $\\rightarrow$ 14 days $\\rightarrow$ 30 days).\n- **Mistake Recycling**: Incorrect ratings reset the repetition interval to 1 day, surfacing the question in tomorrow's review queue.\n- **Privacy First**: All candidate progress, ratings, and custom study plans remain 100% browser-local without mandatory user accounts or telemetry tracking.\n\n### 4.3 Interactive Calculators & Simulators\n\n1. **Roofline Model Engine (`app/roofline/page.tsx`, `lib/hardware.ts`)**:\n   - Calculates arithmetic intensity $\\text{AI} = \\frac{\\text{FLOPs}}{\\text{Bytes}}$ against hardware peak compute ($T_{\\text{peak}}$) and memory bandwidth ($B_{\\text{mem}}$).\n   - Computes the hardware ridge point $I_{\\text{ridge}} = \\frac{T_{\\text{peak}}}{B_{\\text{mem}}}$.\n   - Plots operational points for standard workloads (BERT, ResNet, GPT-2, LLaMA-70B FP16/INT8).\n\n2. **Distributed Training Cluster Simulator (`app/simulator/page.tsx`, `lib/simulator.ts`)**:\n   - Models 3D parallelism: Tensor Parallelism (TP), Pipeline Parallelism (PP), Data Parallelism (DP), and ZeRO-1/2/3.\n   - Calculates per-GPU memory breakdown (Weights, Gradients, Optimizer States, Activation Memory).\n   - Computes Ring AllReduce communication latency across hierarchical networks (NVLink intra-node vs InfiniBand NDR inter-node).\n   - Computes Model FLOPs Utilization (MFU), cluster Mean Time Between Failures (MTBF), and end-to-end training durations.\n\n3. **Radial Sunburst Explorer (`app/explore/page.tsx`)**:\n   - Interactive SVG sunburst visualizer enabling drill-down across Track $\\rightarrow$ Competency Area $\\rightarrow$ Topic $\\rightarrow$ Question Level with search filtering.\n\n---\n\n## 5. Pillar 4: Socratic AI Conductor & Multi-Provider Relay\n\nThe live interview experience (`/interview`) pairs candidates with an AI Socratic interviewer powered by `staffml-vault-worker` and `lib/interview-conductor.ts`.\n\n```mermaid\nsequenceDiagram\n    autonumber\n    actor Candidate as Candidate\n    participant UI as Interview UI (app/interview)\n    participant Cond as Conductor Engine (lib/interview-conductor)\n    participant Worker as Cloudflare Edge Worker\n    participant LLM as LLM Provider Cascade\n\n    Candidate->>UI: Selects Track, Level & Duration (e.g. Cloud L4, 30 min)\n    UI->>Cond: Initializes session & selects entry Socratic Chain\n    Cond->>Worker: POST /interview/turn (System Prompt + Question Context + Transcript)\n    Worker->>LLM: Fallback cascade (Groq ➔ OpenAI ➔ Anthropic ➔ Gemini ➔ Workers AI)\n    LLM-->>Worker: Streaming Response + Structured ---CONDUCTOR_META---\n    Worker-->>UI: Relays SSE stream\n    UI->>Candidate: Renders Socratic response\n    Candidate->>UI: Submits napkin math & architectural answer\n    UI->>Cond: Evaluates answer, adjusts depth, or traverses chain\n    Cond->>Worker: Next turn with rubric feedback criteria\n```\n\n### 5.1 Multi-Provider Fallback Cascade\n\nTo ensure 99.99% uptime and low latency for live mock interviews, the Cloudflare Worker relays requests through a prioritized multi-provider cascade:\n1. **Groq** (`llama-3.3-70b-versatile` / `mixtral-8x7b`): Ultra-low time-to-first-token (<200ms).\n2. **OpenAI** (`gpt-4o` / `gpt-4o-mini`): High-accuracy reasoning fallback.\n3. **Anthropic** (`claude-3-5-sonnet` / `claude-3-5-haiku`): Deep architectural critique.\n4. **Google Gemini** (`gemini-2.0-flash` / `gemini-1.5-pro`): Large context window fallback.\n5. **OpenRouter**: Global dynamic routing fallback.\n6. **Cloudflare Workers AI**: Edge-native, zero-external-dependency final fallback.\n\n### 5.2 Conductor Metadata Protocol\n\nAt each Socratic turn, the AI interviewer appends structured metadata:\n```\n---CONDUCTOR_META---\n{\n  \"intent\": \"probe\",\n  \"score\": 75,\n  \"napkin_math_correct\": true,\n  \"concept_tested\": \"PagedAttention KV cache allocation\",\n  \"advance_chain\": false\n}\n```\n`interview-conductor.ts` parses this block to dynamically decide whether to probe deeper, provide hints, retreat to foundational concepts, or advance to the next question in the chain.\n\n---\n\n## 6. Directory Map\n\n| Path | Purpose |\n| :--- | :--- |\n| **`staffml/vault/`** | The question corpus source of truth: 10,711 YAML files, `chains.json`, `taxonomy.yaml`, `id-registry.yaml`. |\n| **`staffml/vault/schema/`** | LinkML v1.0 schema definitions (`question_schema.yaml`, `enums.py`). |\n| **`staffml/vault/visuals/`** | 144 source SVG architectural and memory diagrams. |\n| **`staffml/vault-cli/`** | Python CLI toolchain (`vault` command) for authoring, invariant checking, building, and publishing. |\n| **`staffml/app/`** | Next.js 16 App Router web application (`src/app/`, `src/components/`, `src/lib/`). |\n| **`staffml/app/worker/`** | Next.js serverless worker relay for LLM conductor streaming. |\n| **`staffml/vault-worker/`** | Cloudflare Edge Worker serving D1 database endpoints and search. |\n| **`staffml/paper/`** | Academic publication macros and LaTeX build scripts synchronized with `vault.db`. |\n\n---\n\n## 7. Verification & Build Contract\n\nTo verify the entire software stack locally:\n\n```bash\n# 1. Verify Vault corpus invariants & health\ncd staffml/vault-cli\npython3 -m pytest -o addopts=\"\" tests/\npython3 -m vault_cli.main check\npython3 -m vault_cli.main doctor\n\n# 2. Compile local corpus and database\npython3 -m vault_cli.main build --local\n\n# 3. Test & build Next.js application\ncd ../staffml\nnpm test\nNEXT_PUBLIC_VAULT_FALLBACK=static npm run build\n\n# 4. Test Cloudflare Edge Worker\ncd ../vault-worker\nnpm test\n```\n","binder/tools/audit/README.md":"# binder/tools/audit — Editorial and Registry Audits\n\nDetection tooling that scans textbook content against the house style rules\nand the MLSys·im registry, plus the verification scripts that back the book\nchecks.\n\n**Fmt / notation audit** (inline `{python}` numbers, spurious `.0`): see\n[`fmt/README.md`](fmt/README.md).\n\n### Registry migration build (constants → zoos)\n\nEnd-to-end gate for the completed `mlsysim` registry migration:\n\n```bash\npython3 binder/tools/audit/check_registry_migration_build.py\n```\n\nIndividual tools:\n\n| Script | Purpose |\n|--------|---------|\n| `book_check_registry_sources.py` | Ban legacy flat constants / alias paths in QMD LEGO cells |\n| `generate_appendix_constants.py --verify` | Execute appendix assumption-table cells against live registries |\n| `refresh_mlsysim_constants_yamls.py --finalize` | Mark audit YAML inventory `should_change: false` |\n| `audit_mlsysim_drift.py` | Detect hand-coded canonical constant drift |\n\n---\n\n## Style scan\n\n```\nbinder/tools/audit/\n├── README.md                      — this file\n├── __init__.py\n├── protected_contexts.py          — LineWalker + inline span detection\n├── ledger.py                      — Issue + Ledger JSON model\n├── scan.py                        — scanner CLI\n├── accept_list.py                 — persistent false-positive accept-list\n├── accepted_fps.json              — accepted false positives\n├── verify.py                      — structural verification checks\n├── math_render/                   — rendered HTML/PDF math-leak audits (see math_render/README.md)\n└── checks/\n    ├── __init__.py\n    ├── vs_period.py               — bare 'vs' → 'vs.'\n    ├── compound_prefix.py         — pre-/non- close-up (strict 6-term list)\n    ├── percent_symbol.py          — '%' → 'percent' in body prose\n    ├── lowercase_prose_references.py  — 'Chapter 12' → 'chapter 12'\n    ├── acknowledgements_spelling.py   — British → American\n    ├── binary_units.py            — GiB/TiB in prose (detection only)\n    └── h3_titlecase.py            — H3+ headings in title case (detection only)\n```\n\nThe scanner is read-only. It reports issues; an editor decides each fix in\ncontext.\n\n### Persistent accept-list\n\n`accept_list.py` + `accepted_fps.json` together record editorial verdicts on\nscanner false positives (proper-noun-heavy headings, named principles,\nlegislation, after-colon CMS 8.158 caps, D·A·M/C³ taxonomy axes). After every\nscan, matching issues are flipped from `open` to `accepted` and tagged with the\nsub-rule that justifies them. Match key is `(category, repo-relative file,\nexact `before` line)` — if a heading is intentionally edited, its accept-list\nentry stops matching and the issue correctly returns to `open` for re-review.\n\n```bash\n# Default: accept-list applied, summary shows matched + stale counts\npython3 binder/tools/audit/scan.py --scope vol1 -v\n\n# Report every issue, ignoring the accept-list\npython3 binder/tools/audit/scan.py --scope vol1 --no-accept-list -v\n\n# Use a different accept-list file (e.g. a draft to iterate on)\npython3 binder/tools/audit/scan.py --scope vol1 --accept-list /tmp/draft.json\n```\n\n### Scan usage\n\nAll commands are from the repo root.\n\n```bash\npython3 binder/tools/audit/scan.py --scope vol2 --verbose\npython3 binder/tools/audit/scan.py --scope vol1 --output vol1-ledger.json --verbose\n```\n\nProduces `audit-ledger.json` (or the path given by `--output`).\n\n---\n\n## Check categories\n\n| Category | Rule | Notes |\n|---|---|---|\n| `vs-period` | §10.10 | Bare `vs` in prose |\n| `compound-prefix-closeup` | §10.8 | Strict 6-term list, no extrapolation |\n| `percent-symbol` | §10.2 | HTML attribute filter (width=N%) |\n| `lowercase-prose-references` | §10.4 | Hand-written \"Chapter 12\" |\n| `acknowledgements-spelling` | §10.7 | British → American |\n| `binary-units-in-prose` | §1 | Detection only |\n| `h3-titlecase` | §10.9 | Per-heading judgment required |\n\n---\n\n## Validation anchors\n\nScan times on a cold run from the repo root:\n\n```\n$ python3 binder/tools/audit/scan.py --scope vol1 -v\nTotal: 629 issues across 34 files (0.4s)\n\n$ python3 binder/tools/audit/scan.py --scope vol2 -v\nTotal: 969 issues across 39 files (0.4s)\n```\n\n### Steady-state anchor (2026-04-08)\n\n| Category | vol1 open | vol1 accepted | vol2 open | vol2 accepted |\n|---|---:|---:|---:|---:|\n| vs-period | 0 | 0 | 0 | 0 |\n| compound-prefix-closeup | 0 | 0 | 0 | 0 |\n| percent-symbol | 0 | 0 | 0 | 0 |\n| lowercase-prose-references | 0 | 0 | 0 | 0 |\n| acknowledgements-spelling | 0 | 0 | 0 | 0 |\n| binary-units-in-prose | 0 | 0 | 0 | 0 |\n| h3-titlecase | **61** | 0 | **29** | 0 |\n| concept-term-capitalization | **19** | 0 | **62** | 0 |\n| abbreviation-first-use | **163** | 0 | **111** | 0 |\n| **TOTAL** | **243** | 0 | **202** | 0 |\n\nItem D uses file-level exclusions for `glossary.qmd` (glossaries are\ndefinitions, not first uses) and excludes the `SIFT` homonym (CV meaning vs\nfault-tolerance meaning).\n\nReproduce with `python3 binder/tools/audit/scan.py --scope vol1 -v`.\nRun the detector self-tests with:\n\n```bash\nPYTHONPATH=binder/tools python3 binder/tools/audit/checks/h3_titlecase.py\nPYTHONPATH=binder/tools python3 binder/tools/audit/checks/concept_term_capitalization.py\nPYTHONPATH=binder/tools python3 binder/tools/audit/checks/abbreviation_first_use.py\n```\n\nExpect `41/41 passed`, `32/32 passed`, and `17/17 passed`.\n\n---\n\n## Adversarial test coverage\n\n- `protected_contexts.py`: 14 adversarial tests covering bold definitions,\n  callout titles, table headers, sentence starts, index entries, @-refs,\n  citations, footnote refs, fig-cap attributes, inline code, and inline math.\n- `compound_prefix.py`: 21 tests covering the strict 6-term list,\n  domain-compound preservation, acronym/proper-noun continuation, and\n  case preservation.\n\nRun the adversarial tests inline with each check module during development.\n","tinytorch/tools/RELEASE_TESTING.md":"# TinyTorch Release Testing\n\nWhat must be true before a release ships, how to check it, and why each check\nexists. Every gate below corresponds to a defect actually found in the\npre-release cleanup of 2026-09 — none are hypothetical.\n\n## Run it\n\n```bash\npython3 tools/release_check.py          # all gates (training tests can take 15+ min)\npython3 tools/release_check.py --fast   # skip the two slow gates (~10 s)\npython3 tools/release_check.py --list   # show gates without running\npython3 tools/release_check.py -k spine # run one gate\n```\n\nExit code is 0 only when every non-advisory gate passes.\n\n`--fast` is the pre-commit loop. The full run is the pre-release gate; it adds\nthe student-journey simulation and the pytest suite, which together take most of\nthe wall time.\n\n---\n\n## The gates\n\n### Structure — every module looks the same\n\nA student who learns the shape of one module should navigate any of the other\nnineteen without relearning it.\n\n| Gate | What it enforces |\n|---|---|\n| 20 modules, numbered 1–20, each with an export target | No gaps, and every module declares `#\\| default_exp` |\n| Imports after Dependencies, before Introduction | Setup cannot execute before its prerequisite explanation (2026-09-11 audit gate) |\n| The 13-section spine, in order | 🔗 Prerequisites → 🎯 Learning Objectives → 📦 Where This Code Lives → 📋 Module Dependencies → 💡 Introduction → 📐 Foundations → 🏗️ Implementation → 🔧 Integration → 📊 Systems Analysis → 🧪 Module Integration Test → 🤔 Reflection Questions → ⭐ Aha Moment → 🚀 MODULE SUMMARY |\n| No duplicate `##` headings | Two identical headings are indistinguishable in the Colab table of contents |\n| Subtitled headings use `: ` | 154 used a colon, 26 used a dash |\n| MODULE SUMMARY subsections, in order | Key Accomplishments → Systems Insights Discovered → Ready for Next Steps → Export with → **Next** |\n\n**The emoji contract.** The emoji is what students internalize, so it must mean\nthe same thing everywhere: 💡 motivation, 📐 theory, 🏗️ things you build, 🔧\nwiring them together, 📊 measurement, 🧪 tests, ⚠️ hazards. Module 15 once marked\nfour sections 🔧 that were each followed by an exercise; module 17 used 🔧 for a\nsection module 14 marks 📊. The spine gate catches missing sections; emoji\nmisuse inside a section is still a human review item.\n\n### nbgrader — the metadata must be honest\n\n| Gate | What it enforces |\n|---|---|\n| Exactly three canonical header shapes | exercise / graded test / given code, nothing else |\n| `solution: true` implies `BEGIN/END SOLUTION` | 56 cells were marked as exercises with nothing to fill in — imports, setup, demos. They survived only because `ClearSolutions.enforce_metadata = False` |\n| `grade_id` unique within a module | Duplicates make nbgrader's mapping ambiguous |\n\nCurrent counts: **155 exercises, 195 graded tests, 73 given cells.** (2026-09-20; these drift every release, so re-measure rather than trusting the number.)\n\n### Pedagogy — the notebook must read\n\n| Gate | What it enforces |\n|---|---|\n| Every exercise has a markdown cell before it | 15 exercises once had none. Module 06 had **seven consecutive** under a heading about a different function |\n| Every unit test has a What/Why/Expected header | 19 of 20 modules did this; module 17 had none |\n| Exercise docstrings carry TODO and APPROACH | The scaffold students follow |\n| Reflection Questions render as markdown | Module 15's was a code cell showing a raw Python string |\n| Unit-test docstrings open with 🧪 | 19 across four modules opened with a bare `Test`, and one still carried the retired 🔬 |\n| An exercise is followed by its test, not by more exercises | A student should not write several components before any is checked. Module 14 asked for nine profiling helpers in a row and tested them 1,100 lines later; module 06 ran to ten. Limit is five, since a family of small classes may legitimately share one test |\n\n### Progressive disclosure — nothing arrives early\n\n| Gate | What it enforces |\n|---|---|\n| No module imports from a later-numbered module | Hard gate. Currently clean |\n| Forward references are framed as previews | **Advisory** — a regex cannot judge a roadmap diagram or a mid-sentence pointer. Read the warnings; do not treat them as failures |\n\n### Package surface — what students import must exist\n\n| Gate | What it enforces |\n|---|---|\n| Every export target imports | All 20 `tinytorch.*` modules load |\n| Every documented import resolves | Each \"Where This Code Lives\" block is executable. This is the gate that caught `OlympicEvent` never being exported because `#\\| export` sat below an import line instead of at the top of its cell |\n| No unreferenced zero-arg demo functions | 16 of 20 modules call their analysis functions under `if __name__ == \"__main__\"` so students see output. Seven were defined and never called. Functions that take arguments are utilities, not demos, and are exempt |\n\n### Tests — a green suite must mean something\n\n| Gate | What it enforces |\n|---|---|\n| No test signals failure with a bare `return` | pytest discards the value. **Thirteen tests could not fail; six were actually failing** |\n| No exception handler asserts success | Missing implementations or incompatible APIs must not become `assert True` (2026-09-11 audit gate) |\n| No bare `except:` | Six swallowed real failures. The worst skipped the gradient update entirely, turning \"the network never trained\" into a pass |\n| No graded cell swallows its own failure | A handler whose body is only a `pass` or a `print` makes the points unreachable. Module 19's ten-point plotting test caught every exception and passed, so the method could draw nothing and still score full marks. The expected-raise idiom is exempt |\n| Every test file imports and collects | Catches a stale import before the suite runs |\n| Source-built reference regressions | Exports all instructor solutions from `src/` into a temporary package and checks graph lifetime, gradients, loss/shape boundaries, optimizer/checkpoint state, profiling, pruning, quantization, distillation, and cached generation; stale local exports cannot hide failures |\n| Notebook inventory | Requires exactly the 20 notebooks corresponding to the sources before attempting the journey |\n\n### Slow gates\n\n| Gate | What it enforces |\n|---|---|\n| Student journey | All 20 instructor notebooks execute end-to-end as `__main__`, each in a fresh interpreter with only earlier modules exported into a temporary package |\n| pytest | The full suite, including the slow training tests, green |\n\nRun `python3 tools/check_reference.py` directly for the numerical regression check.\nIt is also wired into pre-commit and CI. Generate notebooks with\n`python3 -m tito.main dev export --all` before running the journey.\nThis checks the instructor reference progression; student solution stripping\nand completion enforcement are separate concerns.\n\nMilestone accuracy assertions read the named final metric, rather than any\npercentage printed by a script. The CIFAR learning test lives in\n`test_milestones_training.py` and is marked `slow`; construction-only smoke\ntests remain in `test_milestones_smoke.py`.\n\n---\n\n## What the suite itself must not contain\n\nThe gates above police the module sources. The suite under `tests/` is held to\nthe same standard by review, because a test that cannot fail is worse than no\ntest: it occupies the space where a real check would go.\n\nRemoved in the 2026-09 cleanup: a 91-line file with no test functions that\npytest executed as a script on every collection; three files skipped in full\nbecause they tested APIs the framework no longer has; five environment checks\nwhose only reaction to a bad condition was to print a warning; and one CLI check\nwhose own comment said it was informational and would not fail.\n\nFixed at the same time: `--tinytorch`, the educational mode the test README\nrecommends to students, printed `ALL PASSED | 0 passed, 0 total` on a run with\nfailures, because its reporter was never wired to pytest's results.\n\n## Determinism\n\nNineteen `tinytorch` modules carry a module-level `rng = np.random.default_rng(7)`\nthat layer initialization draws from. It is shared and mutable, so how a layer\ninitializes depends on how many draws happened earlier in the session.\n\nTwo tests passed alone and failed inside the suite because of this. Both created\na local `rng = default_rng(7)` believing it seeded `Linear`; it did not, because\n`Linear` reads its own module global. One even carried a comment saying the seed\nwas there to prevent exactly that flake.\n\n`tests/conftest.py` now reseeds all nineteen generators before each test via an\nautouse fixture. **If you add a module with a global RNG, the fixture finds it\nautomatically** — it walks the package rather than using a hardcoded list.\n\nTo confirm order-independence after a change:\n\n```bash\npython3 -m pytest tests/integration/test_training_capabilities.py -q -k xor_learning\npython3 -m pytest tests/integration -q -k xor_learning\npython3 -m pytest tests/ -q --ignore=tests/environment\n```\n\nAll three must agree.\n\n---\n\n## Manual review — what the gates cannot check\n\n1. **Is the explanation any good?** The gates verify a markdown cell exists\n   before each exercise, not that it teaches.\n2. **Is the emoji semantically right?** Enforced for missing sections, not for a\n   section filed under the wrong emoji.\n3. **Grading weights.** Points per exercise currently spans 5.3 (module 06, 21\n   exercises for 111 points) to 50.0 (module 20, two exercises for 100 points).\n   Module totals span 54 (module 15) to 225 (module 19). Deliberate authorial\n   decision, not yet normalized. Re-measure before quoting these; they move\n   every release.\n4. **Book-authored examples and explanatory claims.** Symbol-derived narrative\n   listings are synchronized by `book/tools/listings.py --check`; that\n   does not validate surrounding prose, figures, or separately authored examples.\n\n---\n\n## Adding a gate\n\nWhen a defect is found, add the gate that would have caught it, in\n`tools/release_check.py`:\n\n```python\n@gate(\"category: what must be true\")\ndef g_short_name():\n    errs = []\n    ...                       # append one string per offender\n    return errs               # empty list == pass\n```\n\nUse `slow=True` for anything over a few seconds, and `advisory=True` when the\ncheck is a judgment call that should warn rather than block. The gate's message\nshould name the offender specifically enough to fix without re-deriving it.\n","books/_extensions/README.md":"# MLSysBook Extensions\n\nThis directory contains Quarto extensions used by the MLSysBook project.\n\n## ⚠️ CRITICAL WARNING - READ BEFORE MAKING CHANGES\n\n**Some extensions in this directory are HEAVILY CUSTOMIZED and should NEVER be reinstalled using `quarto add`.**\n\n### 🔍 Quick Safety Check\n\nBefore installing or updating any extension, **ALWAYS** check for:\n1. `.CUSTOM_LOCK` files in extension directories\n2. Version numbers ending in `-mlsysbook-custom`\n3. Warnings in extension `_extension.yml` files\n\n### 📋 Extension Inventory\n\n<table width=\"100%\">\n  <thead>\n<tr>\n<th width=\"40%\"><b>Extension</b></th>\n<th width=\"35%\">Status</th>\n<th width=\"25%\">Safe to Update?</th>\n</tr>\n</thead>\n<tbody>\n<tr><td><b>`margin-video`</b></td><td>🚫 **100% Custom**</td><td>Never (MLSysBook only)</td></tr>\n<tr><td><b>`mlsysbook-ext/pseudocode`</b></td><td>🚫 **Customized** (casing, ▷ comments, EPUB)</td><td>Never</td></tr>\n<tr><td><b>`ute/custom-numbered-blocks`</b></td><td>🚫 **Heavy Customization**</td><td>Never</td></tr>\n<tr><td><b>`nmfs-opensci/titlepage`</b></td><td>🚫 **Customized**</td><td>Never</td></tr>\n<tr><td><b>`pandoc-ext/diagram`</b></td><td>✅ Standard</td><td>Yes</td></tr>\n<tr><td><b>`quarto-ext/lightbox`</b></td><td>✅ Standard</td><td>Yes</td></tr>\n</tbody>\n</table>\n\n### 🚨 Emergency Recovery\n\nIf you accidentally overwrote a custom extension:\n```bash\n# Check what changed\ngit status\n\n# Restore from git if needed\ngit checkout HEAD -- book/_extensions/EXTENSION_NAME/\n\n# Run protection check\npython tools/scripts/check_custom_extensions.py\n```\n\n### 📚 Full Documentation\n\nFor complete details, see: [`CUSTOM_EXTENSIONS.md`](./CUSTOM_EXTENSIONS.md)\n\n---\n**When in doubt, DON'T reinstall - ask the team first!**\n","binder/tools/dependencies/README.md":"# dependencies Documentation\n\nPath: `binder/tools/dependencies/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/dependencies/README.md)","binder/tools/figures/README.md":"# figures Documentation\n\nPath: `binder/tools/figures/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/figures/README.md)","binder/tools/git-hooks/README.md":"# git-hooks Documentation\n\nPath: `binder/tools/git-hooks/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/git-hooks/README.md)","binder/tools/notation/katex_builtins.json":"# Notation Skill\n\nPath: `binder/tools/notation/katex_builtins.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/notation/katex_builtins.json)","binder/tools/notation/package-lock.json":"# Notation Skill\n\nPath: `binder/tools/notation/package-lock.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/notation/package-lock.json)","binder/tools/notation/package.json":"# Notation Skill\n\nPath: `binder/tools/notation/package.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/notation/package.json)","binder/tools/scripts/README.md":"# scripts Documentation\n\nPath: `binder/tools/scripts/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/README.md)","tinytorch/tinytorch/extensions/README.md":"# extensions Documentation\n\nPath: `tinytorch/tinytorch/extensions/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/tinytorch/tinytorch/extensions/README.md)","tinytorch/tools/dev/README.md":"# dev Documentation\n\nPath: `tinytorch/tools/dev/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/tinytorch/tools/dev/README.md)","binder/tools/audit/artifacts/dead_constants_verified.json":"# Artifacts Skill\n\nPath: `binder/tools/audit/artifacts/dead_constants_verified.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/artifacts/dead_constants_verified.json)","binder/tools/audit/artifacts/fmt_design_b_inventory.json":"# Artifacts Skill\n\nPath: `binder/tools/audit/artifacts/fmt_design_b_inventory.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/artifacts/fmt_design_b_inventory.json)","binder/tools/audit/artifacts/registry_migration_manifest.json":"# Artifacts Skill\n\nPath: `binder/tools/audit/artifacts/registry_migration_manifest.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/artifacts/registry_migration_manifest.json)","binder/tools/audit/baselines/captions_baseline.json":"# Baselines Skill\n\nPath: `binder/tools/audit/baselines/captions_baseline.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/baselines/captions_baseline.json)","binder/tools/audit/baselines/scaffold_citation_baseline.json":"# Baselines Skill\n\nPath: `binder/tools/audit/baselines/scaffold_citation_baseline.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/baselines/scaffold_citation_baseline.json)","binder/tools/audit/data/notation_strict_baseline.json":"# Data Skill\n\nPath: `binder/tools/audit/data/notation_strict_baseline.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/notation_strict_baseline.json)","binder/tools/audit/data/terms_registry.json":"# Data Skill\n\nPath: `binder/tools/audit/data/terms_registry.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/terms_registry.json)","binder/tools/audit/data/terms_registry.yaml":"# Data Skill\n\nPath: `binder/tools/audit/data/terms_registry.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/terms_registry.yaml)","binder/tools/audit/fmt/README.md":"# fmt Documentation\n\nPath: `binder/tools/audit/fmt/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/fmt/README.md)","binder/tools/audit/math_render/README.md":"# math_render Documentation\n\nPath: `binder/tools/audit/math_render/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/math_render/README.md)","binder/tools/audits/mlsysim_constants/README.md":"# mlsysim_constants Documentation\n\nPath: `binder/tools/audits/mlsysim_constants/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/README.md)","binder/tools/audits/mlsysim_constants/vol1_appendix_algorithm.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_appendix_algorithm.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_appendix_algorithm.yaml)","binder/tools/audits/mlsysim_constants/vol1_appendix_assumptions.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_appendix_assumptions.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_appendix_assumptions.yaml)","binder/tools/audits/mlsysim_constants/vol1_appendix_dam.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_appendix_dam.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_appendix_dam.yaml)","binder/tools/audits/mlsysim_constants/vol1_appendix_data.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_appendix_data.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_appendix_data.yaml)","binder/tools/audits/mlsysim_constants/vol1_appendix_machine.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_appendix_machine.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_appendix_machine.yaml)","binder/tools/audits/mlsysim_constants/vol1_benchmarking.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_benchmarking.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_benchmarking.yaml)","binder/tools/audits/mlsysim_constants/vol1_conclusion.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_conclusion.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_conclusion.yaml)","binder/tools/audits/mlsysim_constants/vol1_data_engineering.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_data_engineering.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_data_engineering.yaml)","binder/tools/audits/mlsysim_constants/vol1_data_selection.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_data_selection.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_data_selection.yaml)","binder/tools/audits/mlsysim_constants/vol1_frameworks.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_frameworks.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_frameworks.yaml)","binder/tools/audits/mlsysim_constants/vol1_hw_acceleration.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_hw_acceleration.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_hw_acceleration.yaml)","binder/tools/audits/mlsysim_constants/vol1_introduction.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_introduction.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_introduction.yaml)","binder/tools/audits/mlsysim_constants/vol1_ml_lifecycle.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_ml_lifecycle.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_ml_lifecycle.yaml)","binder/tools/audits/mlsysim_constants/vol1_ml_ops.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_ml_ops.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_ml_ops.yaml)","binder/tools/audits/mlsysim_constants/vol1_model_compression.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_model_compression.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_model_compression.yaml)","binder/tools/audits/mlsysim_constants/vol1_model_serving.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_model_serving.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_model_serving.yaml)","binder/tools/audits/mlsysim_constants/vol1_nn_architectures.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_nn_architectures.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_nn_architectures.yaml)","binder/tools/audits/mlsysim_constants/vol1_nn_computation.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_nn_computation.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_nn_computation.yaml)","binder/tools/audits/mlsysim_constants/vol1_responsible_engr.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_responsible_engr.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_responsible_engr.yaml)","binder/tools/audits/mlsysim_constants/vol1_system_paradigms.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_system_paradigms.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_system_paradigms.yaml)","binder/tools/audits/mlsysim_constants/vol1_training.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_training.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_training.yaml)","binder/tools/audits/mlsysim_constants/vol2_appendix_assumptions.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_appendix_assumptions.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_assumptions.yaml)","binder/tools/audits/mlsysim_constants/vol2_appendix_c3.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_appendix_c3.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_c3.yaml)","binder/tools/audits/mlsysim_constants/vol2_appendix_communication.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_appendix_communication.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_communication.yaml)","binder/tools/audits/mlsysim_constants/vol2_appendix_dam.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_appendix_dam.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_dam.yaml)","binder/tools/audits/mlsysim_constants/vol2_appendix_fleet.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_appendix_fleet.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_fleet.yaml)","binder/tools/audits/mlsysim_constants/vol2_appendix_reliability.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_appendix_reliability.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_reliability.yaml)","binder/tools/audits/mlsysim_constants/vol2_collective_communication.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_collective_communication.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_collective_communication.yaml)","binder/tools/audits/mlsysim_constants/vol2_compute_infrastructure.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_compute_infrastructure.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_compute_infrastructure.yaml)","binder/tools/audits/mlsysim_constants/vol2_conclusion.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_conclusion.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_conclusion.yaml)","binder/tools/audits/mlsysim_constants/vol2_data_storage.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_data_storage.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_data_storage.yaml)","binder/tools/audits/mlsysim_constants/vol2_distributed_training.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_distributed_training.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_distributed_training.yaml)","binder/tools/audits/mlsysim_constants/vol2_edge_intelligence.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_edge_intelligence.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_edge_intelligence.yaml)","binder/tools/audits/mlsysim_constants/vol2_fault_tolerance.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_fault_tolerance.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_fault_tolerance.yaml)","binder/tools/audits/mlsysim_constants/vol2_fleet_orchestration.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_fleet_orchestration.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_fleet_orchestration.yaml)","binder/tools/audits/mlsysim_constants/vol2_inference.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_inference.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_inference.yaml)","binder/tools/audits/mlsysim_constants/vol2_introduction.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_introduction.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_introduction.yaml)","binder/tools/audits/mlsysim_constants/vol2_network_fabrics.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_network_fabrics.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_network_fabrics.yaml)","binder/tools/audits/mlsysim_constants/vol2_ops_scale.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_ops_scale.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_ops_scale.yaml)","binder/tools/audits/mlsysim_constants/vol2_performance_engineering.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_performance_engineering.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_performance_engineering.yaml)","binder/tools/audits/mlsysim_constants/vol2_responsible_ai.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_responsible_ai.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_responsible_ai.yaml)","binder/tools/audits/mlsysim_constants/vol2_robust_ai.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_robust_ai.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_robust_ai.yaml)","binder/tools/audits/mlsysim_constants/vol2_security_privacy.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_security_privacy.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_security_privacy.yaml)","binder/tools/audits/mlsysim_constants/vol2_sustainable_ai.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_sustainable_ai.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_sustainable_ai.yaml)","binder/tools/scripts/audit/citation_reference_workflow.md":"# Audit Skill\n\nPath: `binder/tools/scripts/audit/citation_reference_workflow.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/audit/citation_reference_workflow.md)","binder/tools/scripts/content/README.md":"# content Documentation\n\nPath: `binder/tools/scripts/content/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/content/README.md)","binder/tools/scripts/content/README_INDEX_PLACEMENT.md":"# Content Skill\n\nPath: `binder/tools/scripts/content/README_INDEX_PLACEMENT.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/content/README_INDEX_PLACEMENT.md)","binder/tools/scripts/docs/FIGURE_CAPTIONS.md":"# Docs Skill\n\nPath: `binder/tools/scripts/docs/FIGURE_CAPTIONS.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/docs/FIGURE_CAPTIONS.md)","binder/tools/scripts/docs/README.md":"# docs Documentation\n\nPath: `binder/tools/scripts/docs/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/docs/README.md)","binder/tools/scripts/docs/SECTION_ID_SYSTEM.md":"# Docs Skill\n\nPath: `binder/tools/scripts/docs/SECTION_ID_SYSTEM.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/docs/SECTION_ID_SYSTEM.md)","binder/tools/scripts/docs/WORKFLOW_CLEANUP.md":"# Docs Skill\n\nPath: `binder/tools/scripts/docs/WORKFLOW_CLEANUP.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/docs/WORKFLOW_CLEANUP.md)","binder/tools/scripts/images/README.md":"# images Documentation\n\nPath: `binder/tools/scripts/images/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/images/README.md)","binder/tools/scripts/infrastructure/README.md":"# infrastructure Documentation\n\nPath: `binder/tools/scripts/infrastructure/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/infrastructure/README.md)","binder/tools/scripts/mit_press/AU_QUERY_RESPONSES.md":"# Mit_press Skill\n\nPath: `binder/tools/scripts/mit_press/AU_QUERY_RESPONSES.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/mit_press/AU_QUERY_RESPONSES.md)","binder/tools/scripts/socratiQ/README.md":"# socratiQ Documentation\n\nPath: `binder/tools/scripts/socratiQ/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/socratiQ/README.md)","binder/tools/scripts/utilities/README.md":"# utilities Documentation\n\nPath: `binder/tools/scripts/utilities/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/utilities/README.md)","books/_extensions/mlsysbook-ext/margin-video/README.md":"# margin-video Documentation\n\nPath: `books/_extensions/mlsysbook-ext/margin-video/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/books/_extensions/mlsysbook-ext/margin-video/README.md)","tinytorch/guide/tools/diagrams/STYLE.md":"# Diagrams Skill\n\nPath: `tinytorch/guide/tools/diagrams/STYLE.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/tinytorch/guide/tools/diagrams/STYLE.md)","binder/tools/audit/data/chapter_terms/global_backmatter_references.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_backmatter_references.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_backmatter_references.json)","binder/tools/audit/data/chapter_terms/global_backmatter_resources_phd_survival_guide.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_backmatter_resources_phd_survival_guide.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_backmatter_resources_phd_survival_guide.json)","binder/tools/audit/data/chapter_terms/global_frontmatter_about_about.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_frontmatter_about_about.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_frontmatter_about_about.json)","binder/tools/audit/data/chapter_terms/global_frontmatter_acknowledgements_acknowledgements.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_frontmatter_acknowledgements_acknowledgements.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_frontmatter_acknowledgements_acknowledgements.json)","binder/tools/audit/data/chapter_terms/global_frontmatter_index.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_frontmatter_index.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_frontmatter_index.json)","binder/tools/audit/data/chapter_terms/global_frontmatter_socratiq_socratiq.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_frontmatter_socratiq_socratiq.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_frontmatter_socratiq_socratiq.json)","binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_algorithm.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_algorithm.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_algorithm.json)","binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_assumptions.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_assumptions.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_assumptions.json)","binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_dam.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_dam.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_dam.json)","binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_data.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_data.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_data.json)","binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_machine.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_machine.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_machine.json)","binder/tools/audit/data/chapter_terms/vol1_backmatter_glossary_glossary.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_glossary_glossary.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_glossary_glossary.json)","binder/tools/audit/data/chapter_terms/vol1_backmatter_references.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_references.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_references.json)","binder/tools/audit/data/chapter_terms/vol1_benchmarking_benchmarking.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_benchmarking_benchmarking.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_benchmarking_benchmarking.json)","binder/tools/audit/data/chapter_terms/vol1_conclusion_conclusion.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_conclusion_conclusion.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_conclusion_conclusion.json)","binder/tools/audit/data/chapter_terms/vol1_data_engineering_data_engineering.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_data_engineering_data_engineering.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_data_engineering_data_engineering.json)","binder/tools/audit/data/chapter_terms/vol1_data_selection_data_selection.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_data_selection_data_selection.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_data_selection_data_selection.json)","binder/tools/audit/data/chapter_terms/vol1_frameworks_frameworks.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frameworks_frameworks.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frameworks_frameworks.json)","binder/tools/audit/data/chapter_terms/vol1_frontmatter__conventions.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter__conventions.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter__conventions.json)","binder/tools/audit/data/chapter_terms/vol1_frontmatter__notation_body.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter__notation_body.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter__notation_body.json)","binder/tools/audit/data/chapter_terms/vol1_frontmatter_about.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_about.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_about.json)","binder/tools/audit/data/chapter_terms/vol1_frontmatter_acknowledgements.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_acknowledgements.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_acknowledgements.json)","binder/tools/audit/data/chapter_terms/vol1_frontmatter_ai_use.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_ai_use.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_ai_use.json)","binder/tools/audit/data/chapter_terms/vol1_frontmatter_author_note.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_author_note.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_author_note.json)","binder/tools/audit/data/chapter_terms/vol1_frontmatter_dedication.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_dedication.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_dedication.json)","binder/tools/audit/data/chapter_terms/vol1_frontmatter_foreword.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_foreword.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_foreword.json)","binder/tools/audit/data/chapter_terms/vol1_frontmatter_notation.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_notation.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_notation.json)","binder/tools/audit/data/chapter_terms/vol1_hw_acceleration_hw_acceleration.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_hw_acceleration_hw_acceleration.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_hw_acceleration_hw_acceleration.json)","binder/tools/audit/data/chapter_terms/vol1_index.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_index.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_index.json)","binder/tools/audit/data/chapter_terms/vol1_introduction_introduction.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_introduction_introduction.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_introduction_introduction.json)","binder/tools/audit/data/chapter_terms/vol1_ml_lifecycle_ml_lifecycle.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_ml_lifecycle_ml_lifecycle.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_ml_lifecycle_ml_lifecycle.json)","binder/tools/audit/data/chapter_terms/vol1_ml_ops_ml_ops.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_ml_ops_ml_ops.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_ml_ops_ml_ops.json)","binder/tools/audit/data/chapter_terms/vol1_model_compression_model_compression.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_model_compression_model_compression.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_model_compression_model_compression.json)","binder/tools/audit/data/chapter_terms/vol1_model_serving_model_serving.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_model_serving_model_serving.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_model_serving_model_serving.json)","binder/tools/audit/data/chapter_terms/vol1_nn_architectures_nn_architectures.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_nn_architectures_nn_architectures.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_nn_architectures_nn_architectures.json)","binder/tools/audit/data/chapter_terms/vol1_nn_computation_nn_computation.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_nn_computation_nn_computation.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_nn_computation_nn_computation.json)","binder/tools/audit/data/chapter_terms/vol1_parts_build_principles.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_parts_build_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_parts_build_principles.json)","binder/tools/audit/data/chapter_terms/vol1_parts_deploy_principles.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_parts_deploy_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_parts_deploy_principles.json)","binder/tools/audit/data/chapter_terms/vol1_parts_foundations_principles.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_parts_foundations_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_parts_foundations_principles.json)","binder/tools/audit/data/chapter_terms/vol1_parts_optimize_principles.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_parts_optimize_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_parts_optimize_principles.json)","binder/tools/audit/data/chapter_terms/vol1_responsible_engr_responsible_engr.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_responsible_engr_responsible_engr.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_responsible_engr_responsible_engr.json)","binder/tools/audit/data/chapter_terms/vol1_system_paradigms_system_paradigms.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_system_paradigms_system_paradigms.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_system_paradigms_system_paradigms.json)","binder/tools/audit/data/chapter_terms/vol1_training_training.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_training_training.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_training_training.json)","binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_assumptions.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_assumptions.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_assumptions.json)","binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_c3.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_c3.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_c3.json)","binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_communication.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_communication.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_communication.json)","binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_dam.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_dam.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_dam.json)","binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_fleet.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_fleet.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_fleet.json)","binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_inference.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_inference.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_inference.json)","binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_reliability.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_reliability.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_reliability.json)","binder/tools/audit/data/chapter_terms/vol2_backmatter_glossary_glossary.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_glossary_glossary.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_glossary_glossary.json)","binder/tools/audit/data/chapter_terms/vol2_backmatter_references.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_references.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_references.json)","binder/tools/audit/data/chapter_terms/vol2_collective_communication_collective_communication.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_collective_communication_collective_communication.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_collective_communication_collective_communication.json)","binder/tools/audit/data/chapter_terms/vol2_compute_infrastructure_compute_infrastructure.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_compute_infrastructure_compute_infrastructure.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_compute_infrastructure_compute_infrastructure.json)","binder/tools/audit/data/chapter_terms/vol2_conclusion_conclusion.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_conclusion_conclusion.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_conclusion_conclusion.json)","binder/tools/audit/data/chapter_terms/vol2_data_storage_data_storage.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_data_storage_data_storage.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_data_storage_data_storage.json)","binder/tools/audit/data/chapter_terms/vol2_distributed_training_distributed_training.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_distributed_training_distributed_training.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_distributed_training_distributed_training.json)","binder/tools/audit/data/chapter_terms/vol2_edge_intelligence_edge_intelligence.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_edge_intelligence_edge_intelligence.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_edge_intelligence_edge_intelligence.json)","binder/tools/audit/data/chapter_terms/vol2_fault_tolerance_fault_tolerance.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_fault_tolerance_fault_tolerance.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_fault_tolerance_fault_tolerance.json)","binder/tools/audit/data/chapter_terms/vol2_fleet_orchestration_fleet_orchestration.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_fleet_orchestration_fleet_orchestration.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_fleet_orchestration_fleet_orchestration.json)","binder/tools/audit/data/chapter_terms/vol2_frontmatter__notation_scaling.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter__notation_scaling.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter__notation_scaling.json)","binder/tools/audit/data/chapter_terms/vol2_frontmatter_about.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_about.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_about.json)","binder/tools/audit/data/chapter_terms/vol2_frontmatter_acknowledgements.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_acknowledgements.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_acknowledgements.json)","binder/tools/audit/data/chapter_terms/vol2_frontmatter_ai_use.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_ai_use.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_ai_use.json)","binder/tools/audit/data/chapter_terms/vol2_frontmatter_author_note.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_author_note.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_author_note.json)","binder/tools/audit/data/chapter_terms/vol2_frontmatter_dedication.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_dedication.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_dedication.json)","binder/tools/audit/data/chapter_terms/vol2_frontmatter_foreword.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_foreword.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_foreword.json)","binder/tools/audit/data/chapter_terms/vol2_frontmatter_notation.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_notation.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_notation.json)","binder/tools/audit/data/chapter_terms/vol2_index.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_index.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_index.json)","binder/tools/audit/data/chapter_terms/vol2_inference_inference.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_inference_inference.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_inference_inference.json)","binder/tools/audit/data/chapter_terms/vol2_introduction_introduction.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_introduction_introduction.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_introduction_introduction.json)","binder/tools/audit/data/chapter_terms/vol2_network_fabrics_network_fabrics.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_network_fabrics_network_fabrics.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_network_fabrics_network_fabrics.json)","binder/tools/audit/data/chapter_terms/vol2_ops_scale_ops_scale.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_ops_scale_ops_scale.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_ops_scale_ops_scale.json)","binder/tools/audit/data/chapter_terms/vol2_parts_deployment_principles.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_parts_deployment_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_parts_deployment_principles.json)","binder/tools/audit/data/chapter_terms/vol2_parts_distributed_ml_principles.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_parts_distributed_ml_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_parts_distributed_ml_principles.json)","binder/tools/audit/data/chapter_terms/vol2_parts_fleet_principles.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_parts_fleet_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_parts_fleet_principles.json)","binder/tools/audit/data/chapter_terms/vol2_parts_responsible_fleet_principles.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_parts_responsible_fleet_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_parts_responsible_fleet_principles.json)","binder/tools/audit/data/chapter_terms/vol2_performance_engineering_performance_engineering.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_performance_engineering_performance_engineering.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_performance_engineering_performance_engineering.json)","binder/tools/audit/data/chapter_terms/vol2_responsible_ai_responsible_ai.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_responsible_ai_responsible_ai.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_responsible_ai_responsible_ai.json)","binder/tools/audit/data/chapter_terms/vol2_robust_ai_robust_ai.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_robust_ai_robust_ai.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_robust_ai_robust_ai.json)","binder/tools/audit/data/chapter_terms/vol2_security_privacy_security_privacy.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_security_privacy_security_privacy.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_security_privacy_security_privacy.json)","binder/tools/audit/data/chapter_terms/vol2_sustainable_ai_sustainable_ai.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_sustainable_ai_sustainable_ai.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_sustainable_ai_sustainable_ai.json)","binder/tools/audit/data/chapter_terms/vol3_index.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol3_index.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol3_index.json)"},"files":{"binder/tools/README.md":"# MLSysBook Tools\n\n`binder/tools` contains production tooling for the MLSysBook source tree. These\ntools are part of how the book is built, checked, generated, audited, and\nreleased. Some are called by humans, some by CI, some by Binder commands, and\nsome by Quarto-adjacent generation workflows.\n\nDo not delete, rename, or move anything under this tree only because it looks\nlike a one-off script. First audit actual use in QMD files, Binder commands, CI,\nrelease scripts, documentation, and generated-asset workflows.\n\n## Production Policy\n\n- Treat `binder/tools` as book infrastructure, not scratch space.\n- Before relocating or removing a tool, search for call sites with `rg`, update\n  callers and documentation, and run the relevant validation command.\n- Prefer stable modules or Binder-facing entrypoints for new book dependencies.\n  Scripts may remain as compatibility entrypoints when they are already part of\n  production workflows.\n- Generated assets should record their source tool in the nearby README or\n  comments so future editors can regenerate rather than hand-edit them.\n- Tooling that depends on external packages should document the runtime command\n  and any special environment setup.\n\n## Current Areas\n\n| Area | Purpose |\n|---|---|\n| `scripts/` | Python and shell entrypoints for generation, maintenance, release, and Quarto-adjacent workflows. |\n| `audit/` | Durable audit records and audit helpers used to track book quality work. |\n| `dependencies/` | Dependency and environment documentation. |\n| `git-hooks/` | Repository hook documentation and related setup. |\n\n## Figure Tool Ownership\n\nThe matplotlib figure style (palette, font stack, font sizes, figure size, and\nthe `setup_plot()` helper) has one source: `mlsysim/mlsysim/viz/style.py`,\nalongside the simulator-aware plotters in `mlsysim.viz`. Every figure, whether\na chapter cell or an `mlsysim` plotter, inherits the same sizes from it.\n\n```text\nmlsysim/mlsysim/viz/\n  style.py        # COLORS, set_book_style(), setup_plot(), BODY_FIGSIZE, MIN_FONT_PT\n  fonts/          # bundled TeX Gyre Heros faces registered by set_book_style()\nbinder/tools/figures/\n  style.py        # re-export of mlsysim.viz.style (the import path chapter cells use)\n```\n\nChapter cells may import either `binder.tools.figures.style` or `mlsysim.viz`;\nboth resolve to the same objects. Define nothing style-related in binder.\n\n`./binder/binder check figures --scope print-scale --volN` renders every\nmatplotlib body figure and checks it against the limits in `viz/style.py`\n(print scale, minimum font size, figures created without the style).\n","binder/tools/bib_lint_baseline.json":"{\n  \"description\": \"bib_lint allow-list: pre-existing violations grandfathered at the time of the baseline. New violations NOT in this file will block commits. Regenerate via: python3 binder/tools/bib_lint.py --all --baseline\",\n  \"generated\": \"2026-04-08\",\n  \"allowed\": [\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"ahn2022saycan\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"alshiekh2018safe\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"amanatides1987fast\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"ames2014control\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"annpureddy2011staliro\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"assran2023self\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"banerjee2018hands\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"barfoot2017state\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@article missing required field `journal`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"bishop1998methodology\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"brohan2023rt1\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"chen2018tvm\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"cheng2019end\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"codevilla2018offline\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      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\"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 1838,\n    \"message\": \"Closed name embodied_daily_kg_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 3203,\n    \"message\": \"Closed name phone_battery_j_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 3205,\n    \"message\": \"Closed name budget_j_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  }\n]","tinytorch/tools/README.md":"# Development Tools\n\nThis directory contains tools for TinyTorch maintainers and contributors.\n\n## Structure\n\n- **`release_check.py`** - The pre-release gate suite. `--fast` runs the 34 quick\n  gates; the full run adds the top-to-bottom notebook journey and the pytest\n  suite. `--list` prints every gate. See `RELEASE_TESTING.md`.\n- **`check_reference.py`** - Builds the instructor solutions into a temporary\n  package and runs the numerical and training regressions against it, so a stale\n  local export cannot make the check pass.\n- **`validate_nbgrader_config.py`** - Checks the nbgrader cell-header shapes and\n  `grade_id`s across all 20 modules. Expect `Passed: 20, Failed: 0`.\n- **`check_prose_solution_leaks.py`** - Fails if a graded solution is reprinted in\n  prose outside its `BEGIN/END SOLUTION` region.\n- **`check_grading_holes.py`** - Reports graded cells that pass on an empty student\n  notebook, which happens when a cell's assertions only reach regions tagged\n  `role=\"scaffold\"` and therefore shipped pre-solved.\n- **`dev/`** - Development environment setup and utilities.\n\n## For Students\n\nStudents don't need anything in this directory. Use the main setup scripts in the\nproject root.\n\n## For Developers\n\n- `RELEASE_TESTING.md` in this directory describes what each gate covers and what\n  it deliberately does not.\n- `../MODULE_ANATOMY.md` is the specification for how a module is built, and wins\n  whenever a module, a checklist, or an agent prompt disagrees with it.\n- `../CONTRIBUTING.md` covers the branch and release workflow.\n","staffml/ARCHITECTURE.md":"# StaffML Software Architecture\n\n> **High-Level System Architecture & Design Blueprint**\n> **Repository:** `MLSysBook` (`staffml/`)\n> **Platform:** [StaffML (https://mlsysbook.ai/staffml/)](https://mlsysbook.ai/staffml/)\n> **Audience:** Engineers, contributors, and systems researchers inspecting or extending the platform.\n\n---\n\n## 1. System Overview & Philosophy\n\n**StaffML** is an open-source, physics-grounded preparation and evaluation platform for machine learning systems engineers. Unlike conventional software engineering interview prep (which centers on algorithmic complexity and data structures), ML systems interviews require reasoning about physical hardware constraints: memory bandwidth limits, compute rooflines, interconnect bisections, numerical precision, and thermal/power budgets.\n\nThe central design principle of StaffML is:\n> *You can generate the code, but you cannot prompt your way out of a silicon bottleneck.*\n\n```mermaid\ngraph TD\n    subgraph \"1. Source of Truth (Git)\"\n        YAML[\"10,711 Structured YAMLs<br/>staffml/vault/questions/\"]\n        CHAINS[\"843 Socratic Chains<br/>staffml/vault/chains.json\"]\n        TAXONOMY[\"87 Topics & 13 Areas<br/>staffml/vault/taxonomy.yaml\"]\n        REGISTRY[\"Append-Only ID Registry<br/>staffml/vault/id-registry.yaml\"]\n    end\n\n    subgraph \"2. Compiler & Verification Engine\"\n        CLI[\"vault-cli (Python / Typer / Pydantic)\"]\n        CHECK[\"vault check (Fast, Structural & Slow Invariants)\"]\n        BUILD[\"vault build (Parallel Compiler)\"]\n        DB[\"SQLite Database (vault.db)\"]\n        STATIC[\"Static Corpus JSON (corpus.json)\"]\n    end\n\n    subgraph \"3. Serving & Edge Infrastructure\"\n        WORKER[\"Cloudflare Edge Worker (D1 + KV + Vector)\"]\n        LLM_RELAY[\"Multi-Provider LLM Adapter<br/>Groq ➔ OpenAI ➔ Anthropic ➔ Gemini\"]\n    end\n\n    subgraph \"4. Client Application (Next.js 16)\"\n        APP[\"Next.js App Router (16 Routes)\"]\n        PRACTICE[\"Spaced Repetition Practice\"]\n        ROOFLINE[\"Interactive Roofline Engine\"]\n        SIMULATOR[\"3D Parallelism Simulator\"]\n        GAUNTLET[\"Timed Gauntlet Mock Mode\"]\n        CONDUCTOR[\"Live Socratic AI Conductor\"]\n        EXPLORER[\"Radial Sunburst Explorer\"]\n    end\n\n    YAML --> CHECK\n    CHAINS --> CHECK\n    TAXONOMY --> CHECK\n    REGISTRY --> CHECK\n    CHECK --> BUILD\n    BUILD --> DB\n    BUILD --> STATIC\n    DB --> WORKER\n    STATIC --> APP\n    WORKER --> APP\n    APP --> PRACTICE\n    APP --> ROOFLINE\n    APP --> SIMULATOR\n    APP --> GAUNTLET\n    APP --> EXPLORER\n    APP --> CONDUCTOR\n    CONDUCTOR --> LLM_RELAY\n```\n\nThe system is decoupled into four modular pillars:\n1. **The Question Vault**: A human-first, git-tracked corpus of 10,711 validated YAML files conforming to LinkML/Pydantic schemas.\n2. **The Build & Tooling Layer (`vault-cli`)**: A high-performance compiler that validates invariants, tracks content hashes, and compiles SQLite (`vault.db`) and static bundles.\n3. **The Web Application (`app/`)**: A Next.js 16 App Router application supporting dual runtime modes (local static fallback vs edge-connected D1).\n4. **The Edge & LLM Conductor (`vault-worker` & `app/worker`)**: A Cloudflare Edge Worker providing low-latency Socratic mock interviewing via a resilient multi-provider fallback cascade.\n\n---\n\n## 2. Pillar 1: The Question Vault & Data Model\n\n### 2.1 Four-Axis Classification Schema\n\nEvery question in the vault is classified along four orthogonal axes enforced by LinkML schema v1.0 and Pydantic models:\n\n```mermaid\nclassDiagram\n    class Question {\n        +String schema_version\n        +String id\n        +Track track\n        +Level level\n        +Zone zone\n        +String topic\n        +String competency_area\n        +String bloom_level\n        +String title\n        +String scenario\n        +String question\n        +Visual visual\n        +Details details\n        +String status\n        +String provenance\n        +List~ChainRef~ chains\n    }\n\n    class Details {\n        +String realistic_solution\n        +String common_mistake\n        +String napkin_math\n        +List~String~ options\n        +Int correct_index\n        +List~Resource~ resources\n    }\n\n    class Visual {\n        +String kind\n        +String path\n        +String alt\n        +String caption\n    }\n\n    class ChainRef {\n        +String id\n        +Int position\n    }\n\n    Question *-- Details\n    Question o-- Visual\n    Question o-- ChainRef\n```\n\n- **Track (`track`)**: Deployment domain — `cloud`, `edge`, `mobile`, `tinyml`, or `global`.\n- **Level (`level`)**: Bloom's Taxonomy depth — `L1` (Recall), `L2` (Understand), `L3` (Apply), `L4` (Analyze), `L5` (Evaluate), `L6+` (Create/Architect).\n- **Zone (`zone`)**: 11 Ikigai problem zones — `recall`, `fluency`, `implement`, `analyze`, `diagnosis`, `specification`, `evaluation`, `mastery`, `optimization`, `design`, `realization`.\n- **Competency Area (`competency_area`)**: 13 technical disciplines — `architecture`, `compute`, `memory`, `networking`, `optimization`, `deployment`, `latency`, `power`, `precision`, `reliability`, `data`, `parallelism`, `cross-cutting`.\n\n### 2.2 Socratic Chains\n\nQuestions do not exist in isolation; they are linked into **Socratic Chains** (`staffml/vault/chains.json`). A chain represents a pedagogical progression through an ML systems problem:\n1. **Entry Point (L1/L2)**: Establishes baseline facts (e.g. GPU memory bandwidth or FlashAttention tile size).\n2. **Application & Math (L3)**: Requires arithmetic derivation (e.g. arithmetic intensity or KV cache sizing).\n3. **System Breakdown & Analysis (L4/L5)**: Diagnoses bottlenecks under scale (e.g. pipeline bubbles, NCCL ring contention, thermal throttling).\n4. **Architecture & Synthesis (L6+)**: Evaluates holistic trade-offs under competing constraints.\n\nChains support two progression tiers:\n- **Primary Tier**: Strict Bloom monotonic progression ($\\Delta \\in \\{1, 2\\}$).\n- **Secondary Tier**: Lenient coverage sweeps ($\\Delta \\in \\{0, 1, 2, 3\\}$).\n\n### 2.3 Cryptographic Integrity & Merkle Release Hashes\n\nEvery question receives a deterministic `content_hash` (SHA-256 over normalized canonical JSON of semantic fields). Releases compute a **Merkle root** (`release_hash`) over all published question hashes, taxonomy, chains, zones, and release policy. This provides cryptographic verification for academic citation and drift detection across deployments.\n\n---\n\n## 3. Pillar 2: The CLI & Compiler (`vault-cli`)\n\n`vault-cli` is a typed Python package built with Typer and Rich.\n\n```\nvault-cli/\n├── src/vault_cli/\n│   ├── main.py             # CLI entry point\n│   ├── loader.py           # Parallel YAML filesystem loader + sidecar chain joiner\n│   ├── validator.py        # Multi-tier invariant validation\n│   ├── compiler.py         # SQLite / D1 compiler (compiles vault.db)\n│   ├── models.py           # Pydantic schema models\n│   ├── hashing.py          # Deterministic SHA-256 & Merkle tree calculation\n│   ├── legacy_export.py    # Generates public/data/corpus.json\n│   └── commands/           # check, doctor, build, publish, ship, new, promote\n└── tests/                  # Pytest test suite (97 tests)\n```\n\n### 3.1 Invariant Validation Tiers\n\n`vault check` executes three validation tiers:\n- **Fast Tier (<1s)**: Schema validation, unique ID registry check, path lowercase conventions, required fields.\n- **Structural Tier (<10s)**: Cross-references between taxonomy, topics, chains, 3-part `common_mistake` markers (`**The Pitfall:**`, `**The Rationale:**`, `**The Consequence:**`), `napkin_math` structure, and visual asset existence.\n- **Slow Tier**: Link-rot checks across external documentation URLs and LLM math verification.\n\n---\n\n## 4. Pillar 3: Web Application Architecture (`app/`)\n\nThe frontend is built with **Next.js 16 (App Router)**, TypeScript, Tailwind CSS, KaTeX, and Framer Motion.\n\n```mermaid\ngraph LR\n    subgraph \"Data Access Layer (lib/corpus.ts)\"\n        CONFIG{\"vault-config.ts<br/>(static vs worker)\"}\n        LOCAL[\"Fetch /data/corpus.json<br/>(Static Bundle)\"]\n        REMOTE[\"Fetch Cloudflare Worker API<br/>(D1 Queries)\"]\n        CONFIG -->|Static Mode| LOCAL\n        CONFIG -->|Worker Mode| REMOTE\n    end\n\n    subgraph \"Interactive Modules\"\n        SR[\"Spaced Repetition<br/>(lib/progress.ts)\"]\n        ROOF[\"Roofline Engine<br/>(lib/hardware.ts)\"]\n        SIM[\"3D Sim Engine<br/>(lib/simulator.ts)\"]\n        COND[\"AI Conductor<br/>(lib/interview-conductor.ts)\"]\n    end\n\n    LOCAL --> SR\n    REMOTE --> SR\n    SR --> ROOF\n    SR --> SIM\n    SR --> COND\n```\n\n### 4.1 Dual-Mode Runtime Architecture\n\nThe web application supports two runtime modes via `src/lib/vault-config.ts`:\n1. **Worker Mode (`worker`)**: Light initial page load. Fetches catalog metadata initially and retrieves heavy fields (`scenario`, `details.*`) lazily from the Cloudflare Worker API.\n2. **Static Mode (`static`)**: Fully offline-capable and zero-dependency. Bundles the compiled `corpus.json` in `public/data/` for standalone local deployment or static hosting.\n\n### 4.2 Spaced Repetition Engine (`lib/progress.ts`)\n\nStaffML implements an adapted SuperMemo SM-2 spaced repetition algorithm stored locally in browser `localStorage`:\n- **Interval Progression**: Successful recalls advance review intervals (1 day $\\rightarrow$ 3 days $\\rightarrow$ 7 days $\\rightarrow$ 14 days $\\rightarrow$ 30 days).\n- **Mistake Recycling**: Incorrect ratings reset the repetition interval to 1 day, surfacing the question in tomorrow's review queue.\n- **Privacy First**: All candidate progress, ratings, and custom study plans remain 100% browser-local without mandatory user accounts or telemetry tracking.\n\n### 4.3 Interactive Calculators & Simulators\n\n1. **Roofline Model Engine (`app/roofline/page.tsx`, `lib/hardware.ts`)**:\n   - Calculates arithmetic intensity $\\text{AI} = \\frac{\\text{FLOPs}}{\\text{Bytes}}$ against hardware peak compute ($T_{\\text{peak}}$) and memory bandwidth ($B_{\\text{mem}}$).\n   - Computes the hardware ridge point $I_{\\text{ridge}} = \\frac{T_{\\text{peak}}}{B_{\\text{mem}}}$.\n   - Plots operational points for standard workloads (BERT, ResNet, GPT-2, LLaMA-70B FP16/INT8).\n\n2. **Distributed Training Cluster Simulator (`app/simulator/page.tsx`, `lib/simulator.ts`)**:\n   - Models 3D parallelism: Tensor Parallelism (TP), Pipeline Parallelism (PP), Data Parallelism (DP), and ZeRO-1/2/3.\n   - Calculates per-GPU memory breakdown (Weights, Gradients, Optimizer States, Activation Memory).\n   - Computes Ring AllReduce communication latency across hierarchical networks (NVLink intra-node vs InfiniBand NDR inter-node).\n   - Computes Model FLOPs Utilization (MFU), cluster Mean Time Between Failures (MTBF), and end-to-end training durations.\n\n3. **Radial Sunburst Explorer (`app/explore/page.tsx`)**:\n   - Interactive SVG sunburst visualizer enabling drill-down across Track $\\rightarrow$ Competency Area $\\rightarrow$ Topic $\\rightarrow$ Question Level with search filtering.\n\n---\n\n## 5. Pillar 4: Socratic AI Conductor & Multi-Provider Relay\n\nThe live interview experience (`/interview`) pairs candidates with an AI Socratic interviewer powered by `staffml-vault-worker` and `lib/interview-conductor.ts`.\n\n```mermaid\nsequenceDiagram\n    autonumber\n    actor Candidate as Candidate\n    participant UI as Interview UI (app/interview)\n    participant Cond as Conductor Engine (lib/interview-conductor)\n    participant Worker as Cloudflare Edge Worker\n    participant LLM as LLM Provider Cascade\n\n    Candidate->>UI: Selects Track, Level & Duration (e.g. Cloud L4, 30 min)\n    UI->>Cond: Initializes session & selects entry Socratic Chain\n    Cond->>Worker: POST /interview/turn (System Prompt + Question Context + Transcript)\n    Worker->>LLM: Fallback cascade (Groq ➔ OpenAI ➔ Anthropic ➔ Gemini ➔ Workers AI)\n    LLM-->>Worker: Streaming Response + Structured ---CONDUCTOR_META---\n    Worker-->>UI: Relays SSE stream\n    UI->>Candidate: Renders Socratic response\n    Candidate->>UI: Submits napkin math & architectural answer\n    UI->>Cond: Evaluates answer, adjusts depth, or traverses chain\n    Cond->>Worker: Next turn with rubric feedback criteria\n```\n\n### 5.1 Multi-Provider Fallback Cascade\n\nTo ensure 99.99% uptime and low latency for live mock interviews, the Cloudflare Worker relays requests through a prioritized multi-provider cascade:\n1. **Groq** (`llama-3.3-70b-versatile` / `mixtral-8x7b`): Ultra-low time-to-first-token (<200ms).\n2. **OpenAI** (`gpt-4o` / `gpt-4o-mini`): High-accuracy reasoning fallback.\n3. **Anthropic** (`claude-3-5-sonnet` / `claude-3-5-haiku`): Deep architectural critique.\n4. **Google Gemini** (`gemini-2.0-flash` / `gemini-1.5-pro`): Large context window fallback.\n5. **OpenRouter**: Global dynamic routing fallback.\n6. **Cloudflare Workers AI**: Edge-native, zero-external-dependency final fallback.\n\n### 5.2 Conductor Metadata Protocol\n\nAt each Socratic turn, the AI interviewer appends structured metadata:\n```\n---CONDUCTOR_META---\n{\n  \"intent\": \"probe\",\n  \"score\": 75,\n  \"napkin_math_correct\": true,\n  \"concept_tested\": \"PagedAttention KV cache allocation\",\n  \"advance_chain\": false\n}\n```\n`interview-conductor.ts` parses this block to dynamically decide whether to probe deeper, provide hints, retreat to foundational concepts, or advance to the next question in the chain.\n\n---\n\n## 6. Directory Map\n\n| Path | Purpose |\n| :--- | :--- |\n| **`staffml/vault/`** | The question corpus source of truth: 10,711 YAML files, `chains.json`, `taxonomy.yaml`, `id-registry.yaml`. |\n| **`staffml/vault/schema/`** | LinkML v1.0 schema definitions (`question_schema.yaml`, `enums.py`). |\n| **`staffml/vault/visuals/`** | 144 source SVG architectural and memory diagrams. |\n| **`staffml/vault-cli/`** | Python CLI toolchain (`vault` command) for authoring, invariant checking, building, and publishing. |\n| **`staffml/app/`** | Next.js 16 App Router web application (`src/app/`, `src/components/`, `src/lib/`). |\n| **`staffml/app/worker/`** | Next.js serverless worker relay for LLM conductor streaming. |\n| **`staffml/vault-worker/`** | Cloudflare Edge Worker serving D1 database endpoints and search. |\n| **`staffml/paper/`** | Academic publication macros and LaTeX build scripts synchronized with `vault.db`. |\n\n---\n\n## 7. Verification & Build Contract\n\nTo verify the entire software stack locally:\n\n```bash\n# 1. Verify Vault corpus invariants & health\ncd staffml/vault-cli\npython3 -m pytest -o addopts=\"\" tests/\npython3 -m vault_cli.main check\npython3 -m vault_cli.main doctor\n\n# 2. Compile local corpus and database\npython3 -m vault_cli.main build --local\n\n# 3. Test & build Next.js application\ncd ../staffml\nnpm test\nNEXT_PUBLIC_VAULT_FALLBACK=static npm run build\n\n# 4. Test Cloudflare Edge Worker\ncd ../vault-worker\nnpm test\n```\n","binder/tools/audit/README.md":"# binder/tools/audit — Editorial and Registry Audits\n\nDetection tooling that scans textbook content against the house style rules\nand the MLSys·im registry, plus the verification scripts that back the book\nchecks.\n\n**Fmt / notation audit** (inline `{python}` numbers, spurious `.0`): see\n[`fmt/README.md`](fmt/README.md).\n\n### Registry migration build (constants → zoos)\n\nEnd-to-end gate for the completed `mlsysim` registry migration:\n\n```bash\npython3 binder/tools/audit/check_registry_migration_build.py\n```\n\nIndividual tools:\n\n| Script | Purpose |\n|--------|---------|\n| `book_check_registry_sources.py` | Ban legacy flat constants / alias paths in QMD LEGO cells |\n| `generate_appendix_constants.py --verify` | Execute appendix assumption-table cells against live registries |\n| `refresh_mlsysim_constants_yamls.py --finalize` | Mark audit YAML inventory `should_change: false` |\n| `audit_mlsysim_drift.py` | Detect hand-coded canonical constant drift |\n\n---\n\n## Style scan\n\n```\nbinder/tools/audit/\n├── README.md                      — this file\n├── __init__.py\n├── protected_contexts.py          — LineWalker + inline span detection\n├── ledger.py                      — Issue + Ledger JSON model\n├── scan.py                        — scanner CLI\n├── accept_list.py                 — persistent false-positive accept-list\n├── accepted_fps.json              — accepted false positives\n├── verify.py                      — structural verification checks\n├── math_render/                   — rendered HTML/PDF math-leak audits (see math_render/README.md)\n└── checks/\n    ├── __init__.py\n    ├── vs_period.py               — bare 'vs' → 'vs.'\n    ├── compound_prefix.py         — pre-/non- close-up (strict 6-term list)\n    ├── percent_symbol.py          — '%' → 'percent' in body prose\n    ├── lowercase_prose_references.py  — 'Chapter 12' → 'chapter 12'\n    ├── acknowledgements_spelling.py   — British → American\n    ├── binary_units.py            — GiB/TiB in prose (detection only)\n    └── h3_titlecase.py            — H3+ headings in title case (detection only)\n```\n\nThe scanner is read-only. It reports issues; an editor decides each fix in\ncontext.\n\n### Persistent accept-list\n\n`accept_list.py` + `accepted_fps.json` together record editorial verdicts on\nscanner false positives (proper-noun-heavy headings, named principles,\nlegislation, after-colon CMS 8.158 caps, D·A·M/C³ taxonomy axes). After every\nscan, matching issues are flipped from `open` to `accepted` and tagged with the\nsub-rule that justifies them. Match key is `(category, repo-relative file,\nexact `before` line)` — if a heading is intentionally edited, its accept-list\nentry stops matching and the issue correctly returns to `open` for re-review.\n\n```bash\n# Default: accept-list applied, summary shows matched + stale counts\npython3 binder/tools/audit/scan.py --scope vol1 -v\n\n# Report every issue, ignoring the accept-list\npython3 binder/tools/audit/scan.py --scope vol1 --no-accept-list -v\n\n# Use a different accept-list file (e.g. a draft to iterate on)\npython3 binder/tools/audit/scan.py --scope vol1 --accept-list /tmp/draft.json\n```\n\n### Scan usage\n\nAll commands are from the repo root.\n\n```bash\npython3 binder/tools/audit/scan.py --scope vol2 --verbose\npython3 binder/tools/audit/scan.py --scope vol1 --output vol1-ledger.json --verbose\n```\n\nProduces `audit-ledger.json` (or the path given by `--output`).\n\n---\n\n## Check categories\n\n| Category | Rule | Notes |\n|---|---|---|\n| `vs-period` | §10.10 | Bare `vs` in prose |\n| `compound-prefix-closeup` | §10.8 | Strict 6-term list, no extrapolation |\n| `percent-symbol` | §10.2 | HTML attribute filter (width=N%) |\n| `lowercase-prose-references` | §10.4 | Hand-written \"Chapter 12\" |\n| `acknowledgements-spelling` | §10.7 | British → American |\n| `binary-units-in-prose` | §1 | Detection only |\n| `h3-titlecase` | §10.9 | Per-heading judgment required |\n\n---\n\n## Validation anchors\n\nScan times on a cold run from the repo root:\n\n```\n$ python3 binder/tools/audit/scan.py --scope vol1 -v\nTotal: 629 issues across 34 files (0.4s)\n\n$ python3 binder/tools/audit/scan.py --scope vol2 -v\nTotal: 969 issues across 39 files (0.4s)\n```\n\n### Steady-state anchor (2026-04-08)\n\n| Category | vol1 open | vol1 accepted | vol2 open | vol2 accepted |\n|---|---:|---:|---:|---:|\n| vs-period | 0 | 0 | 0 | 0 |\n| compound-prefix-closeup | 0 | 0 | 0 | 0 |\n| percent-symbol | 0 | 0 | 0 | 0 |\n| lowercase-prose-references | 0 | 0 | 0 | 0 |\n| acknowledgements-spelling | 0 | 0 | 0 | 0 |\n| binary-units-in-prose | 0 | 0 | 0 | 0 |\n| h3-titlecase | **61** | 0 | **29** | 0 |\n| concept-term-capitalization | **19** | 0 | **62** | 0 |\n| abbreviation-first-use | **163** | 0 | **111** | 0 |\n| **TOTAL** | **243** | 0 | **202** | 0 |\n\nItem D uses file-level exclusions for `glossary.qmd` (glossaries are\ndefinitions, not first uses) and excludes the `SIFT` homonym (CV meaning vs\nfault-tolerance meaning).\n\nReproduce with `python3 binder/tools/audit/scan.py --scope vol1 -v`.\nRun the detector self-tests with:\n\n```bash\nPYTHONPATH=binder/tools python3 binder/tools/audit/checks/h3_titlecase.py\nPYTHONPATH=binder/tools python3 binder/tools/audit/checks/concept_term_capitalization.py\nPYTHONPATH=binder/tools python3 binder/tools/audit/checks/abbreviation_first_use.py\n```\n\nExpect `41/41 passed`, `32/32 passed`, and `17/17 passed`.\n\n---\n\n## Adversarial test coverage\n\n- `protected_contexts.py`: 14 adversarial tests covering bold definitions,\n  callout titles, table headers, sentence starts, index entries, @-refs,\n  citations, footnote refs, fig-cap attributes, inline code, and inline math.\n- `compound_prefix.py`: 21 tests covering the strict 6-term list,\n  domain-compound preservation, acronym/proper-noun continuation, and\n  case preservation.\n\nRun the adversarial tests inline with each check module during development.\n","tinytorch/tools/RELEASE_TESTING.md":"# TinyTorch Release Testing\n\nWhat must be true before a release ships, how to check it, and why each check\nexists. Every gate below corresponds to a defect actually found in the\npre-release cleanup of 2026-09 — none are hypothetical.\n\n## Run it\n\n```bash\npython3 tools/release_check.py          # all gates (training tests can take 15+ min)\npython3 tools/release_check.py --fast   # skip the two slow gates (~10 s)\npython3 tools/release_check.py --list   # show gates without running\npython3 tools/release_check.py -k spine # run one gate\n```\n\nExit code is 0 only when every non-advisory gate passes.\n\n`--fast` is the pre-commit loop. The full run is the pre-release gate; it adds\nthe student-journey simulation and the pytest suite, which together take most of\nthe wall time.\n\n---\n\n## The gates\n\n### Structure — every module looks the same\n\nA student who learns the shape of one module should navigate any of the other\nnineteen without relearning it.\n\n| Gate | What it enforces |\n|---|---|\n| 20 modules, numbered 1–20, each with an export target | No gaps, and every module declares `#\\| default_exp` |\n| Imports after Dependencies, before Introduction | Setup cannot execute before its prerequisite explanation (2026-09-11 audit gate) |\n| The 13-section spine, in order | 🔗 Prerequisites → 🎯 Learning Objectives → 📦 Where This Code Lives → 📋 Module Dependencies → 💡 Introduction → 📐 Foundations → 🏗️ Implementation → 🔧 Integration → 📊 Systems Analysis → 🧪 Module Integration Test → 🤔 Reflection Questions → ⭐ Aha Moment → 🚀 MODULE SUMMARY |\n| No duplicate `##` headings | Two identical headings are indistinguishable in the Colab table of contents |\n| Subtitled headings use `: ` | 154 used a colon, 26 used a dash |\n| MODULE SUMMARY subsections, in order | Key Accomplishments → Systems Insights Discovered → Ready for Next Steps → Export with → **Next** |\n\n**The emoji contract.** The emoji is what students internalize, so it must mean\nthe same thing everywhere: 💡 motivation, 📐 theory, 🏗️ things you build, 🔧\nwiring them together, 📊 measurement, 🧪 tests, ⚠️ hazards. Module 15 once marked\nfour sections 🔧 that were each followed by an exercise; module 17 used 🔧 for a\nsection module 14 marks 📊. The spine gate catches missing sections; emoji\nmisuse inside a section is still a human review item.\n\n### nbgrader — the metadata must be honest\n\n| Gate | What it enforces |\n|---|---|\n| Exactly three canonical header shapes | exercise / graded test / given code, nothing else |\n| `solution: true` implies `BEGIN/END SOLUTION` | 56 cells were marked as exercises with nothing to fill in — imports, setup, demos. They survived only because `ClearSolutions.enforce_metadata = False` |\n| `grade_id` unique within a module | Duplicates make nbgrader's mapping ambiguous |\n\nCurrent counts: **155 exercises, 195 graded tests, 73 given cells.** (2026-09-20; these drift every release, so re-measure rather than trusting the number.)\n\n### Pedagogy — the notebook must read\n\n| Gate | What it enforces |\n|---|---|\n| Every exercise has a markdown cell before it | 15 exercises once had none. Module 06 had **seven consecutive** under a heading about a different function |\n| Every unit test has a What/Why/Expected header | 19 of 20 modules did this; module 17 had none |\n| Exercise docstrings carry TODO and APPROACH | The scaffold students follow |\n| Reflection Questions render as markdown | Module 15's was a code cell showing a raw Python string |\n| Unit-test docstrings open with 🧪 | 19 across four modules opened with a bare `Test`, and one still carried the retired 🔬 |\n| An exercise is followed by its test, not by more exercises | A student should not write several components before any is checked. Module 14 asked for nine profiling helpers in a row and tested them 1,100 lines later; module 06 ran to ten. Limit is five, since a family of small classes may legitimately share one test |\n\n### Progressive disclosure — nothing arrives early\n\n| Gate | What it enforces |\n|---|---|\n| No module imports from a later-numbered module | Hard gate. Currently clean |\n| Forward references are framed as previews | **Advisory** — a regex cannot judge a roadmap diagram or a mid-sentence pointer. Read the warnings; do not treat them as failures |\n\n### Package surface — what students import must exist\n\n| Gate | What it enforces |\n|---|---|\n| Every export target imports | All 20 `tinytorch.*` modules load |\n| Every documented import resolves | Each \"Where This Code Lives\" block is executable. This is the gate that caught `OlympicEvent` never being exported because `#\\| export` sat below an import line instead of at the top of its cell |\n| No unreferenced zero-arg demo functions | 16 of 20 modules call their analysis functions under `if __name__ == \"__main__\"` so students see output. Seven were defined and never called. Functions that take arguments are utilities, not demos, and are exempt |\n\n### Tests — a green suite must mean something\n\n| Gate | What it enforces |\n|---|---|\n| No test signals failure with a bare `return` | pytest discards the value. **Thirteen tests could not fail; six were actually failing** |\n| No exception handler asserts success | Missing implementations or incompatible APIs must not become `assert True` (2026-09-11 audit gate) |\n| No bare `except:` | Six swallowed real failures. The worst skipped the gradient update entirely, turning \"the network never trained\" into a pass |\n| No graded cell swallows its own failure | A handler whose body is only a `pass` or a `print` makes the points unreachable. Module 19's ten-point plotting test caught every exception and passed, so the method could draw nothing and still score full marks. The expected-raise idiom is exempt |\n| Every test file imports and collects | Catches a stale import before the suite runs |\n| Source-built reference regressions | Exports all instructor solutions from `src/` into a temporary package and checks graph lifetime, gradients, loss/shape boundaries, optimizer/checkpoint state, profiling, pruning, quantization, distillation, and cached generation; stale local exports cannot hide failures |\n| Notebook inventory | Requires exactly the 20 notebooks corresponding to the sources before attempting the journey |\n\n### Slow gates\n\n| Gate | What it enforces |\n|---|---|\n| Student journey | All 20 instructor notebooks execute end-to-end as `__main__`, each in a fresh interpreter with only earlier modules exported into a temporary package |\n| pytest | The full suite, including the slow training tests, green |\n\nRun `python3 tools/check_reference.py` directly for the numerical regression check.\nIt is also wired into pre-commit and CI. Generate notebooks with\n`python3 -m tito.main dev export --all` before running the journey.\nThis checks the instructor reference progression; student solution stripping\nand completion enforcement are separate concerns.\n\nMilestone accuracy assertions read the named final metric, rather than any\npercentage printed by a script. The CIFAR learning test lives in\n`test_milestones_training.py` and is marked `slow`; construction-only smoke\ntests remain in `test_milestones_smoke.py`.\n\n---\n\n## What the suite itself must not contain\n\nThe gates above police the module sources. The suite under `tests/` is held to\nthe same standard by review, because a test that cannot fail is worse than no\ntest: it occupies the space where a real check would go.\n\nRemoved in the 2026-09 cleanup: a 91-line file with no test functions that\npytest executed as a script on every collection; three files skipped in full\nbecause they tested APIs the framework no longer has; five environment checks\nwhose only reaction to a bad condition was to print a warning; and one CLI check\nwhose own comment said it was informational and would not fail.\n\nFixed at the same time: `--tinytorch`, the educational mode the test README\nrecommends to students, printed `ALL PASSED | 0 passed, 0 total` on a run with\nfailures, because its reporter was never wired to pytest's results.\n\n## Determinism\n\nNineteen `tinytorch` modules carry a module-level `rng = np.random.default_rng(7)`\nthat layer initialization draws from. It is shared and mutable, so how a layer\ninitializes depends on how many draws happened earlier in the session.\n\nTwo tests passed alone and failed inside the suite because of this. Both created\na local `rng = default_rng(7)` believing it seeded `Linear`; it did not, because\n`Linear` reads its own module global. One even carried a comment saying the seed\nwas there to prevent exactly that flake.\n\n`tests/conftest.py` now reseeds all nineteen generators before each test via an\nautouse fixture. **If you add a module with a global RNG, the fixture finds it\nautomatically** — it walks the package rather than using a hardcoded list.\n\nTo confirm order-independence after a change:\n\n```bash\npython3 -m pytest tests/integration/test_training_capabilities.py -q -k xor_learning\npython3 -m pytest tests/integration -q -k xor_learning\npython3 -m pytest tests/ -q --ignore=tests/environment\n```\n\nAll three must agree.\n\n---\n\n## Manual review — what the gates cannot check\n\n1. **Is the explanation any good?** The gates verify a markdown cell exists\n   before each exercise, not that it teaches.\n2. **Is the emoji semantically right?** Enforced for missing sections, not for a\n   section filed under the wrong emoji.\n3. **Grading weights.** Points per exercise currently spans 5.3 (module 06, 21\n   exercises for 111 points) to 50.0 (module 20, two exercises for 100 points).\n   Module totals span 54 (module 15) to 225 (module 19). Deliberate authorial\n   decision, not yet normalized. Re-measure before quoting these; they move\n   every release.\n4. **Book-authored examples and explanatory claims.** Symbol-derived narrative\n   listings are synchronized by `book/tools/listings.py --check`; that\n   does not validate surrounding prose, figures, or separately authored examples.\n\n---\n\n## Adding a gate\n\nWhen a defect is found, add the gate that would have caught it, in\n`tools/release_check.py`:\n\n```python\n@gate(\"category: what must be true\")\ndef g_short_name():\n    errs = []\n    ...                       # append one string per offender\n    return errs               # empty list == pass\n```\n\nUse `slow=True` for anything over a few seconds, and `advisory=True` when the\ncheck is a judgment call that should warn rather than block. The gate's message\nshould name the offender specifically enough to fix without re-deriving it.\n","books/_extensions/README.md":"# MLSysBook Extensions\n\nThis directory contains Quarto extensions used by the MLSysBook project.\n\n## ⚠️ CRITICAL WARNING - READ BEFORE MAKING CHANGES\n\n**Some extensions in this directory are HEAVILY CUSTOMIZED and should NEVER be reinstalled using `quarto add`.**\n\n### 🔍 Quick Safety Check\n\nBefore installing or updating any extension, **ALWAYS** check for:\n1. `.CUSTOM_LOCK` files in extension directories\n2. Version numbers ending in `-mlsysbook-custom`\n3. Warnings in extension `_extension.yml` files\n\n### 📋 Extension Inventory\n\n<table width=\"100%\">\n  <thead>\n<tr>\n<th width=\"40%\"><b>Extension</b></th>\n<th width=\"35%\">Status</th>\n<th width=\"25%\">Safe to Update?</th>\n</tr>\n</thead>\n<tbody>\n<tr><td><b>`margin-video`</b></td><td>🚫 **100% Custom**</td><td>Never (MLSysBook only)</td></tr>\n<tr><td><b>`mlsysbook-ext/pseudocode`</b></td><td>🚫 **Customized** (casing, ▷ comments, EPUB)</td><td>Never</td></tr>\n<tr><td><b>`ute/custom-numbered-blocks`</b></td><td>🚫 **Heavy Customization**</td><td>Never</td></tr>\n<tr><td><b>`nmfs-opensci/titlepage`</b></td><td>🚫 **Customized**</td><td>Never</td></tr>\n<tr><td><b>`pandoc-ext/diagram`</b></td><td>✅ Standard</td><td>Yes</td></tr>\n<tr><td><b>`quarto-ext/lightbox`</b></td><td>✅ Standard</td><td>Yes</td></tr>\n</tbody>\n</table>\n\n### 🚨 Emergency Recovery\n\nIf you accidentally overwrote a custom extension:\n```bash\n# Check what changed\ngit status\n\n# Restore from git if needed\ngit checkout HEAD -- book/_extensions/EXTENSION_NAME/\n\n# Run protection check\npython tools/scripts/check_custom_extensions.py\n```\n\n### 📚 Full Documentation\n\nFor complete details, see: [`CUSTOM_EXTENSIONS.md`](./CUSTOM_EXTENSIONS.md)\n\n---\n**When in doubt, DON'T reinstall - ask the team first!**\n","binder/tools/dependencies/README.md":"# dependencies Documentation\n\nPath: `binder/tools/dependencies/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/dependencies/README.md)","binder/tools/figures/README.md":"# figures Documentation\n\nPath: `binder/tools/figures/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/figures/README.md)","binder/tools/git-hooks/README.md":"# git-hooks Documentation\n\nPath: `binder/tools/git-hooks/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/git-hooks/README.md)","binder/tools/notation/katex_builtins.json":"# Notation Skill\n\nPath: `binder/tools/notation/katex_builtins.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/notation/katex_builtins.json)","binder/tools/notation/package-lock.json":"# Notation Skill\n\nPath: `binder/tools/notation/package-lock.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/notation/package-lock.json)","binder/tools/notation/package.json":"# Notation Skill\n\nPath: `binder/tools/notation/package.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/notation/package.json)","binder/tools/scripts/README.md":"# scripts Documentation\n\nPath: `binder/tools/scripts/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/README.md)","tinytorch/tinytorch/extensions/README.md":"# extensions Documentation\n\nPath: `tinytorch/tinytorch/extensions/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/tinytorch/tinytorch/extensions/README.md)","tinytorch/tools/dev/README.md":"# dev Documentation\n\nPath: `tinytorch/tools/dev/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/tinytorch/tools/dev/README.md)","binder/tools/audit/artifacts/dead_constants_verified.json":"# Artifacts Skill\n\nPath: `binder/tools/audit/artifacts/dead_constants_verified.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/artifacts/dead_constants_verified.json)","binder/tools/audit/artifacts/fmt_design_b_inventory.json":"# Artifacts Skill\n\nPath: `binder/tools/audit/artifacts/fmt_design_b_inventory.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/artifacts/fmt_design_b_inventory.json)","binder/tools/audit/artifacts/registry_migration_manifest.json":"# Artifacts Skill\n\nPath: `binder/tools/audit/artifacts/registry_migration_manifest.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/artifacts/registry_migration_manifest.json)","binder/tools/audit/baselines/captions_baseline.json":"# Baselines Skill\n\nPath: `binder/tools/audit/baselines/captions_baseline.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/baselines/captions_baseline.json)","binder/tools/audit/baselines/scaffold_citation_baseline.json":"# Baselines Skill\n\nPath: `binder/tools/audit/baselines/scaffold_citation_baseline.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/baselines/scaffold_citation_baseline.json)","binder/tools/audit/data/notation_strict_baseline.json":"# Data Skill\n\nPath: `binder/tools/audit/data/notation_strict_baseline.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/notation_strict_baseline.json)","binder/tools/audit/data/terms_registry.json":"# Data Skill\n\nPath: `binder/tools/audit/data/terms_registry.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/terms_registry.json)","binder/tools/audit/data/terms_registry.yaml":"# Data Skill\n\nPath: `binder/tools/audit/data/terms_registry.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/terms_registry.yaml)","binder/tools/audit/fmt/README.md":"# fmt Documentation\n\nPath: `binder/tools/audit/fmt/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/fmt/README.md)","binder/tools/audit/math_render/README.md":"# math_render Documentation\n\nPath: `binder/tools/audit/math_render/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/math_render/README.md)","binder/tools/audits/mlsysim_constants/README.md":"# mlsysim_constants Documentation\n\nPath: `binder/tools/audits/mlsysim_constants/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/README.md)","binder/tools/audits/mlsysim_constants/vol1_appendix_algorithm.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_appendix_algorithm.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_appendix_algorithm.yaml)","binder/tools/audits/mlsysim_constants/vol1_appendix_assumptions.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_appendix_assumptions.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_appendix_assumptions.yaml)","binder/tools/audits/mlsysim_constants/vol1_appendix_dam.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_appendix_dam.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_appendix_dam.yaml)","binder/tools/audits/mlsysim_constants/vol1_appendix_data.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_appendix_data.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_appendix_data.yaml)","binder/tools/audits/mlsysim_constants/vol1_appendix_machine.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_appendix_machine.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_appendix_machine.yaml)","binder/tools/audits/mlsysim_constants/vol1_benchmarking.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_benchmarking.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_benchmarking.yaml)","binder/tools/audits/mlsysim_constants/vol1_conclusion.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_conclusion.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_conclusion.yaml)","binder/tools/audits/mlsysim_constants/vol1_data_engineering.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_data_engineering.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_data_engineering.yaml)","binder/tools/audits/mlsysim_constants/vol1_data_selection.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_data_selection.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_data_selection.yaml)","binder/tools/audits/mlsysim_constants/vol1_frameworks.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_frameworks.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_frameworks.yaml)","binder/tools/audits/mlsysim_constants/vol1_hw_acceleration.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_hw_acceleration.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_hw_acceleration.yaml)","binder/tools/audits/mlsysim_constants/vol1_introduction.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_introduction.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_introduction.yaml)","binder/tools/audits/mlsysim_constants/vol1_ml_lifecycle.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_ml_lifecycle.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_ml_lifecycle.yaml)","binder/tools/audits/mlsysim_constants/vol1_ml_ops.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_ml_ops.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_ml_ops.yaml)","binder/tools/audits/mlsysim_constants/vol1_model_compression.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_model_compression.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_model_compression.yaml)","binder/tools/audits/mlsysim_constants/vol1_model_serving.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_model_serving.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_model_serving.yaml)","binder/tools/audits/mlsysim_constants/vol1_nn_architectures.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_nn_architectures.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_nn_architectures.yaml)","binder/tools/audits/mlsysim_constants/vol1_nn_computation.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_nn_computation.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_nn_computation.yaml)","binder/tools/audits/mlsysim_constants/vol1_responsible_engr.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_responsible_engr.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_responsible_engr.yaml)","binder/tools/audits/mlsysim_constants/vol1_system_paradigms.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_system_paradigms.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_system_paradigms.yaml)","binder/tools/audits/mlsysim_constants/vol1_training.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_training.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_training.yaml)","binder/tools/audits/mlsysim_constants/vol2_appendix_assumptions.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_appendix_assumptions.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_assumptions.yaml)","binder/tools/audits/mlsysim_constants/vol2_appendix_c3.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_appendix_c3.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_c3.yaml)","binder/tools/audits/mlsysim_constants/vol2_appendix_communication.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_appendix_communication.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_communication.yaml)","binder/tools/audits/mlsysim_constants/vol2_appendix_dam.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_appendix_dam.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_dam.yaml)","binder/tools/audits/mlsysim_constants/vol2_appendix_fleet.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_appendix_fleet.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_fleet.yaml)","binder/tools/audits/mlsysim_constants/vol2_appendix_reliability.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_appendix_reliability.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_reliability.yaml)","binder/tools/audits/mlsysim_constants/vol2_collective_communication.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_collective_communication.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_collective_communication.yaml)","binder/tools/audits/mlsysim_constants/vol2_compute_infrastructure.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_compute_infrastructure.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_compute_infrastructure.yaml)","binder/tools/audits/mlsysim_constants/vol2_conclusion.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_conclusion.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_conclusion.yaml)","binder/tools/audits/mlsysim_constants/vol2_data_storage.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_data_storage.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_data_storage.yaml)","binder/tools/audits/mlsysim_constants/vol2_distributed_training.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_distributed_training.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_distributed_training.yaml)","binder/tools/audits/mlsysim_constants/vol2_edge_intelligence.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_edge_intelligence.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_edge_intelligence.yaml)","binder/tools/audits/mlsysim_constants/vol2_fault_tolerance.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_fault_tolerance.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_fault_tolerance.yaml)","binder/tools/audits/mlsysim_constants/vol2_fleet_orchestration.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_fleet_orchestration.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_fleet_orchestration.yaml)","binder/tools/audits/mlsysim_constants/vol2_inference.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_inference.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_inference.yaml)","binder/tools/audits/mlsysim_constants/vol2_introduction.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_introduction.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_introduction.yaml)","binder/tools/audits/mlsysim_constants/vol2_network_fabrics.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_network_fabrics.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_network_fabrics.yaml)","binder/tools/audits/mlsysim_constants/vol2_ops_scale.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_ops_scale.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_ops_scale.yaml)","binder/tools/audits/mlsysim_constants/vol2_performance_engineering.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_performance_engineering.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_performance_engineering.yaml)","binder/tools/audits/mlsysim_constants/vol2_responsible_ai.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_responsible_ai.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_responsible_ai.yaml)","binder/tools/audits/mlsysim_constants/vol2_robust_ai.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_robust_ai.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_robust_ai.yaml)","binder/tools/audits/mlsysim_constants/vol2_security_privacy.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_security_privacy.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_security_privacy.yaml)","binder/tools/audits/mlsysim_constants/vol2_sustainable_ai.yaml":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_sustainable_ai.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_sustainable_ai.yaml)","binder/tools/scripts/audit/citation_reference_workflow.md":"# Audit Skill\n\nPath: `binder/tools/scripts/audit/citation_reference_workflow.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/audit/citation_reference_workflow.md)","binder/tools/scripts/content/README.md":"# content Documentation\n\nPath: `binder/tools/scripts/content/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/content/README.md)","binder/tools/scripts/content/README_INDEX_PLACEMENT.md":"# Content Skill\n\nPath: `binder/tools/scripts/content/README_INDEX_PLACEMENT.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/content/README_INDEX_PLACEMENT.md)","binder/tools/scripts/docs/FIGURE_CAPTIONS.md":"# Docs Skill\n\nPath: `binder/tools/scripts/docs/FIGURE_CAPTIONS.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/docs/FIGURE_CAPTIONS.md)","binder/tools/scripts/docs/README.md":"# docs Documentation\n\nPath: `binder/tools/scripts/docs/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/docs/README.md)","binder/tools/scripts/docs/SECTION_ID_SYSTEM.md":"# Docs Skill\n\nPath: `binder/tools/scripts/docs/SECTION_ID_SYSTEM.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/docs/SECTION_ID_SYSTEM.md)","binder/tools/scripts/docs/WORKFLOW_CLEANUP.md":"# Docs Skill\n\nPath: `binder/tools/scripts/docs/WORKFLOW_CLEANUP.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/docs/WORKFLOW_CLEANUP.md)","binder/tools/scripts/images/README.md":"# images Documentation\n\nPath: `binder/tools/scripts/images/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/images/README.md)","binder/tools/scripts/infrastructure/README.md":"# infrastructure Documentation\n\nPath: `binder/tools/scripts/infrastructure/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/infrastructure/README.md)","binder/tools/scripts/mit_press/AU_QUERY_RESPONSES.md":"# Mit_press Skill\n\nPath: `binder/tools/scripts/mit_press/AU_QUERY_RESPONSES.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/mit_press/AU_QUERY_RESPONSES.md)","binder/tools/scripts/socratiQ/README.md":"# socratiQ Documentation\n\nPath: `binder/tools/scripts/socratiQ/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/socratiQ/README.md)","binder/tools/scripts/utilities/README.md":"# utilities Documentation\n\nPath: `binder/tools/scripts/utilities/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/utilities/README.md)","books/_extensions/mlsysbook-ext/margin-video/README.md":"# margin-video Documentation\n\nPath: `books/_extensions/mlsysbook-ext/margin-video/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/books/_extensions/mlsysbook-ext/margin-video/README.md)","tinytorch/guide/tools/diagrams/STYLE.md":"# Diagrams Skill\n\nPath: `tinytorch/guide/tools/diagrams/STYLE.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/tinytorch/guide/tools/diagrams/STYLE.md)","binder/tools/audit/data/chapter_terms/global_backmatter_references.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_backmatter_references.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_backmatter_references.json)","binder/tools/audit/data/chapter_terms/global_backmatter_resources_phd_survival_guide.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_backmatter_resources_phd_survival_guide.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_backmatter_resources_phd_survival_guide.json)","binder/tools/audit/data/chapter_terms/global_frontmatter_about_about.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_frontmatter_about_about.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_frontmatter_about_about.json)","binder/tools/audit/data/chapter_terms/global_frontmatter_acknowledgements_acknowledgements.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_frontmatter_acknowledgements_acknowledgements.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_frontmatter_acknowledgements_acknowledgements.json)","binder/tools/audit/data/chapter_terms/global_frontmatter_index.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_frontmatter_index.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_frontmatter_index.json)","binder/tools/audit/data/chapter_terms/global_frontmatter_socratiq_socratiq.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_frontmatter_socratiq_socratiq.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_frontmatter_socratiq_socratiq.json)","binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_algorithm.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_algorithm.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_algorithm.json)","binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_assumptions.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_assumptions.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_assumptions.json)","binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_dam.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_dam.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_dam.json)","binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_data.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_data.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_data.json)","binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_machine.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_machine.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_machine.json)","binder/tools/audit/data/chapter_terms/vol1_backmatter_glossary_glossary.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_glossary_glossary.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_glossary_glossary.json)","binder/tools/audit/data/chapter_terms/vol1_backmatter_references.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_references.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_references.json)","binder/tools/audit/data/chapter_terms/vol1_benchmarking_benchmarking.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_benchmarking_benchmarking.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_benchmarking_benchmarking.json)","binder/tools/audit/data/chapter_terms/vol1_conclusion_conclusion.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_conclusion_conclusion.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_conclusion_conclusion.json)","binder/tools/audit/data/chapter_terms/vol1_data_engineering_data_engineering.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_data_engineering_data_engineering.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_data_engineering_data_engineering.json)","binder/tools/audit/data/chapter_terms/vol1_data_selection_data_selection.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_data_selection_data_selection.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_data_selection_data_selection.json)","binder/tools/audit/data/chapter_terms/vol1_frameworks_frameworks.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frameworks_frameworks.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frameworks_frameworks.json)","binder/tools/audit/data/chapter_terms/vol1_frontmatter__conventions.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter__conventions.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter__conventions.json)","binder/tools/audit/data/chapter_terms/vol1_frontmatter__notation_body.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter__notation_body.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter__notation_body.json)","binder/tools/audit/data/chapter_terms/vol1_frontmatter_about.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_about.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_about.json)","binder/tools/audit/data/chapter_terms/vol1_frontmatter_acknowledgements.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_acknowledgements.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_acknowledgements.json)","binder/tools/audit/data/chapter_terms/vol1_frontmatter_ai_use.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_ai_use.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_ai_use.json)","binder/tools/audit/data/chapter_terms/vol1_frontmatter_author_note.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_author_note.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_author_note.json)","binder/tools/audit/data/chapter_terms/vol1_frontmatter_dedication.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_dedication.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_dedication.json)","binder/tools/audit/data/chapter_terms/vol1_frontmatter_foreword.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_foreword.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_foreword.json)","binder/tools/audit/data/chapter_terms/vol1_frontmatter_notation.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_notation.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_notation.json)","binder/tools/audit/data/chapter_terms/vol1_hw_acceleration_hw_acceleration.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_hw_acceleration_hw_acceleration.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_hw_acceleration_hw_acceleration.json)","binder/tools/audit/data/chapter_terms/vol1_index.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_index.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_index.json)","binder/tools/audit/data/chapter_terms/vol1_introduction_introduction.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_introduction_introduction.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_introduction_introduction.json)","binder/tools/audit/data/chapter_terms/vol1_ml_lifecycle_ml_lifecycle.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_ml_lifecycle_ml_lifecycle.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_ml_lifecycle_ml_lifecycle.json)","binder/tools/audit/data/chapter_terms/vol1_ml_ops_ml_ops.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_ml_ops_ml_ops.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_ml_ops_ml_ops.json)","binder/tools/audit/data/chapter_terms/vol1_model_compression_model_compression.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_model_compression_model_compression.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_model_compression_model_compression.json)","binder/tools/audit/data/chapter_terms/vol1_model_serving_model_serving.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_model_serving_model_serving.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_model_serving_model_serving.json)","binder/tools/audit/data/chapter_terms/vol1_nn_architectures_nn_architectures.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_nn_architectures_nn_architectures.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_nn_architectures_nn_architectures.json)","binder/tools/audit/data/chapter_terms/vol1_nn_computation_nn_computation.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_nn_computation_nn_computation.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_nn_computation_nn_computation.json)","binder/tools/audit/data/chapter_terms/vol1_parts_build_principles.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_parts_build_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_parts_build_principles.json)","binder/tools/audit/data/chapter_terms/vol1_parts_deploy_principles.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_parts_deploy_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_parts_deploy_principles.json)","binder/tools/audit/data/chapter_terms/vol1_parts_foundations_principles.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_parts_foundations_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_parts_foundations_principles.json)","binder/tools/audit/data/chapter_terms/vol1_parts_optimize_principles.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_parts_optimize_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_parts_optimize_principles.json)","binder/tools/audit/data/chapter_terms/vol1_responsible_engr_responsible_engr.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_responsible_engr_responsible_engr.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_responsible_engr_responsible_engr.json)","binder/tools/audit/data/chapter_terms/vol1_system_paradigms_system_paradigms.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_system_paradigms_system_paradigms.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_system_paradigms_system_paradigms.json)","binder/tools/audit/data/chapter_terms/vol1_training_training.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_training_training.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_training_training.json)","binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_assumptions.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_assumptions.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_assumptions.json)","binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_c3.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_c3.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_c3.json)","binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_communication.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_communication.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_communication.json)","binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_dam.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_dam.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_dam.json)","binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_fleet.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_fleet.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_fleet.json)","binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_inference.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_inference.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_inference.json)","binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_reliability.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_reliability.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_reliability.json)","binder/tools/audit/data/chapter_terms/vol2_backmatter_glossary_glossary.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_glossary_glossary.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_glossary_glossary.json)","binder/tools/audit/data/chapter_terms/vol2_backmatter_references.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_references.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_references.json)","binder/tools/audit/data/chapter_terms/vol2_collective_communication_collective_communication.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_collective_communication_collective_communication.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_collective_communication_collective_communication.json)","binder/tools/audit/data/chapter_terms/vol2_compute_infrastructure_compute_infrastructure.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_compute_infrastructure_compute_infrastructure.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_compute_infrastructure_compute_infrastructure.json)","binder/tools/audit/data/chapter_terms/vol2_conclusion_conclusion.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_conclusion_conclusion.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_conclusion_conclusion.json)","binder/tools/audit/data/chapter_terms/vol2_data_storage_data_storage.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_data_storage_data_storage.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_data_storage_data_storage.json)","binder/tools/audit/data/chapter_terms/vol2_distributed_training_distributed_training.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_distributed_training_distributed_training.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_distributed_training_distributed_training.json)","binder/tools/audit/data/chapter_terms/vol2_edge_intelligence_edge_intelligence.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_edge_intelligence_edge_intelligence.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_edge_intelligence_edge_intelligence.json)","binder/tools/audit/data/chapter_terms/vol2_fault_tolerance_fault_tolerance.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_fault_tolerance_fault_tolerance.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_fault_tolerance_fault_tolerance.json)","binder/tools/audit/data/chapter_terms/vol2_fleet_orchestration_fleet_orchestration.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_fleet_orchestration_fleet_orchestration.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_fleet_orchestration_fleet_orchestration.json)","binder/tools/audit/data/chapter_terms/vol2_frontmatter__notation_scaling.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter__notation_scaling.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter__notation_scaling.json)","binder/tools/audit/data/chapter_terms/vol2_frontmatter_about.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_about.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_about.json)","binder/tools/audit/data/chapter_terms/vol2_frontmatter_acknowledgements.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_acknowledgements.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_acknowledgements.json)","binder/tools/audit/data/chapter_terms/vol2_frontmatter_ai_use.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_ai_use.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_ai_use.json)","binder/tools/audit/data/chapter_terms/vol2_frontmatter_author_note.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_author_note.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_author_note.json)","binder/tools/audit/data/chapter_terms/vol2_frontmatter_dedication.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_dedication.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_dedication.json)","binder/tools/audit/data/chapter_terms/vol2_frontmatter_foreword.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_foreword.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_foreword.json)","binder/tools/audit/data/chapter_terms/vol2_frontmatter_notation.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_notation.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_notation.json)","binder/tools/audit/data/chapter_terms/vol2_index.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_index.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_index.json)","binder/tools/audit/data/chapter_terms/vol2_inference_inference.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_inference_inference.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_inference_inference.json)","binder/tools/audit/data/chapter_terms/vol2_introduction_introduction.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_introduction_introduction.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_introduction_introduction.json)","binder/tools/audit/data/chapter_terms/vol2_network_fabrics_network_fabrics.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_network_fabrics_network_fabrics.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_network_fabrics_network_fabrics.json)","binder/tools/audit/data/chapter_terms/vol2_ops_scale_ops_scale.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_ops_scale_ops_scale.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_ops_scale_ops_scale.json)","binder/tools/audit/data/chapter_terms/vol2_parts_deployment_principles.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_parts_deployment_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_parts_deployment_principles.json)","binder/tools/audit/data/chapter_terms/vol2_parts_distributed_ml_principles.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_parts_distributed_ml_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_parts_distributed_ml_principles.json)","binder/tools/audit/data/chapter_terms/vol2_parts_fleet_principles.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_parts_fleet_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_parts_fleet_principles.json)","binder/tools/audit/data/chapter_terms/vol2_parts_responsible_fleet_principles.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_parts_responsible_fleet_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_parts_responsible_fleet_principles.json)","binder/tools/audit/data/chapter_terms/vol2_performance_engineering_performance_engineering.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_performance_engineering_performance_engineering.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_performance_engineering_performance_engineering.json)","binder/tools/audit/data/chapter_terms/vol2_responsible_ai_responsible_ai.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_responsible_ai_responsible_ai.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_responsible_ai_responsible_ai.json)","binder/tools/audit/data/chapter_terms/vol2_robust_ai_robust_ai.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_robust_ai_robust_ai.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_robust_ai_robust_ai.json)","binder/tools/audit/data/chapter_terms/vol2_security_privacy_security_privacy.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_security_privacy_security_privacy.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_security_privacy_security_privacy.json)","binder/tools/audit/data/chapter_terms/vol2_sustainable_ai_sustainable_ai.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_sustainable_ai_sustainable_ai.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_sustainable_ai_sustainable_ai.json)","binder/tools/audit/data/chapter_terms/vol3_index.json":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol3_index.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol3_index.json)"},"items":[{"name":"ARCHITECTURE.md","path":"staffml/ARCHITECTURE.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/staffml/ARCHITECTURE.md","title":"staffml - System Architecture & Module Boundaries","category":"project-spec","format":"markdown","content":"# StaffML Software Architecture\n\n> **High-Level System Architecture & Design Blueprint**\n> **Repository:** `MLSysBook` (`staffml/`)\n> **Platform:** [StaffML (https://mlsysbook.ai/staffml/)](https://mlsysbook.ai/staffml/)\n> **Audience:** Engineers, contributors, and systems researchers inspecting or extending the platform.\n\n---\n\n## 1. System Overview & Philosophy\n\n**StaffML** is an open-source, physics-grounded preparation and evaluation platform for machine learning systems engineers. Unlike conventional software engineering interview prep (which centers on algorithmic complexity and data structures), ML systems interviews require reasoning about physical hardware constraints: memory bandwidth limits, compute rooflines, interconnect bisections, numerical precision, and thermal/power budgets.\n\nThe central design principle of StaffML is:\n> *You can generate the code, but you cannot prompt your way out of a silicon bottleneck.*\n\n```mermaid\ngraph TD\n    subgraph \"1. Source of Truth (Git)\"\n        YAML[\"10,711 Structured YAMLs<br/>staffml/vault/questions/\"]\n        CHAINS[\"843 Socratic Chains<br/>staffml/vault/chains.json\"]\n        TAXONOMY[\"87 Topics & 13 Areas<br/>staffml/vault/taxonomy.yaml\"]\n        REGISTRY[\"Append-Only ID Registry<br/>staffml/vault/id-registry.yaml\"]\n    end\n\n    subgraph \"2. Compiler & Verification Engine\"\n        CLI[\"vault-cli (Python / Typer / Pydantic)\"]\n        CHECK[\"vault check (Fast, Structural & Slow Invariants)\"]\n        BUILD[\"vault build (Parallel Compiler)\"]\n        DB[\"SQLite Database (vault.db)\"]\n        STATIC[\"Static Corpus JSON (corpus.json)\"]\n    end\n\n    subgraph \"3. Serving & Edge Infrastructure\"\n        WORKER[\"Cloudflare Edge Worker (D1 + KV + Vector)\"]\n        LLM_RELAY[\"Multi-Provider LLM Adapter<br/>Groq ➔ OpenAI ➔ Anthropic ➔ Gemini\"]\n    end\n\n    subgraph \"4. Client Application (Next.js 16)\"\n        APP[\"Next.js App Router (16 Routes)\"]\n        PRACTICE[\"Spaced Repetition Practice\"]\n        ROOFLINE[\"Interactive Roofline Engine\"]\n        SIMULATOR[\"3D Parallelism Simulator\"]\n        GAUNTLET[\"Timed Gauntlet Mock Mode\"]\n        CONDUCTOR[\"Live Socratic AI Conductor\"]\n        EXPLORER[\"Radial Sunburst Explorer\"]\n    end\n\n    YAML --> CHECK\n    CHAINS --> CHECK\n    TAXONOMY --> CHECK\n    REGISTRY --> CHECK\n    CHECK --> BUILD\n    BUILD --> DB\n    BUILD --> STATIC\n    DB --> WORKER\n    STATIC --> APP\n    WORKER --> APP\n    APP --> PRACTICE\n    APP --> ROOFLINE\n    APP --> SIMULATOR\n    APP --> GAUNTLET\n    APP --> EXPLORER\n    APP --> CONDUCTOR\n    CONDUCTOR --> LLM_RELAY\n```\n\nThe system is decoupled into four modular pillars:\n1. **The Question Vault**: A human-first, git-tracked corpus of 10,711 validated YAML files conforming to LinkML/Pydantic schemas.\n2. **The Build & Tooling Layer (`vault-cli`)**: A high-performance compiler that validates invariants, tracks content hashes, and compiles SQLite (`vault.db`) and static bundles.\n3. **The Web Application (`app/`)**: A Next.js 16 App Router application supporting dual runtime modes (local static fallback vs edge-connected D1).\n4. **The Edge & LLM Conductor (`vault-worker` & `app/worker`)**: A Cloudflare Edge Worker providing low-latency Socratic mock interviewing via a resilient multi-provider fallback cascade.\n\n---\n\n## 2. Pillar 1: The Question Vault & Data Model\n\n### 2.1 Four-Axis Classification Schema\n\nEvery question in the vault is classified along four orthogonal axes enforced by LinkML schema v1.0 and Pydantic models:\n\n```mermaid\nclassDiagram\n    class Question {\n        +String schema_version\n        +String id\n        +Track track\n        +Level level\n        +Zone zone\n        +String topic\n        +String competency_area\n        +String bloom_level\n        +String title\n        +String scenario\n        +String question\n        +Visual visual\n        +Details details\n        +String status\n        +String provenance\n        +List~ChainRef~ chains\n    }\n\n    class Details {\n        +String realistic_solution\n        +String common_mistake\n        +String napkin_math\n        +List~String~ options\n        +Int correct_index\n        +List~Resource~ resources\n    }\n\n    class Visual {\n        +String kind\n        +String path\n        +String alt\n        +String caption\n    }\n\n    class ChainRef {\n        +String id\n        +Int position\n    }\n\n    Question *-- Details\n    Question o-- Visual\n    Question o-- ChainRef\n```\n\n- **Track (`track`)**: Deployment domain — `cloud`, `edge`, `mobile`, `tinyml`, or `global`.\n- **Level (`level`)**: Bloom's Taxonomy depth — `L1` (Recall), `L2` (Understand), `L3` (Apply), `L4` (Analyze), `L5` (Evaluate), `L6+` (Create/Architect).\n- **Zone (`zone`)**: 11 Ikigai problem zones — `recall`, `fluency`, `implement`, `analyze`, `diagnosis`, `specification`, `evaluation`, `mastery`, `optimization`, `design`, `realization`.\n- **Competency Area (`competency_area`)**: 13 technical disciplines — `architecture`, `compute`, `memory`, `networking`, `optimization`, `deployment`, `latency`, `power`, `precision`, `reliability`, `data`, `parallelism`, `cross-cutting`.\n\n### 2.2 Socratic Chains\n\nQuestions do not exist in isolation; they are linked into **Socratic Chains** (`staffml/vault/chains.json`). A chain represents a pedagogical progression through an ML systems problem:\n1. **Entry Point (L1/L2)**: Establishes baseline facts (e.g. GPU memory bandwidth or FlashAttention tile size).\n2. **Application & Math (L3)**: Requires arithmetic derivation (e.g. arithmetic intensity or KV cache sizing).\n3. **System Breakdown & Analysis (L4/L5)**: Diagnoses bottlenecks under scale (e.g. pipeline bubbles, NCCL ring contention, thermal throttling).\n4. **Architecture & Synthesis (L6+)**: Evaluates holistic trade-offs under competing constraints.\n\nChains support two progression tiers:\n- **Primary Tier**: Strict Bloom monotonic progression ($\\Delta \\in \\{1, 2\\}$).\n- **Secondary Tier**: Lenient coverage sweeps ($\\Delta \\in \\{0, 1, 2, 3\\}$).\n\n### 2.3 Cryptographic Integrity & Merkle Release Hashes\n\nEvery question receives a deterministic `content_hash` (SHA-256 over normalized canonical JSON of semantic fields). Releases compute a **Merkle root** (`release_hash`) over all published question hashes, taxonomy, chains, zones, and release policy. This provides cryptographic verification for academic citation and drift detection across deployments.\n\n---\n\n## 3. Pillar 2: The CLI & Compiler (`vault-cli`)\n\n`vault-cli` is a typed Python package built with Typer and Rich.\n\n```\nvault-cli/\n├── src/vault_cli/\n│   ├── main.py             # CLI entry point\n│   ├── loader.py           # Parallel YAML filesystem loader + sidecar chain joiner\n│   ├── validator.py        # Multi-tier invariant validation\n│   ├── compiler.py         # SQLite / D1 compiler (compiles vault.db)\n│   ├── models.py           # Pydantic schema models\n│   ├── hashing.py          # Deterministic SHA-256 & Merkle tree calculation\n│   ├── legacy_export.py    # Generates public/data/corpus.json\n│   └── commands/           # check, doctor, build, publish, ship, new, promote\n└── tests/                  # Pytest test suite (97 tests)\n```\n\n### 3.1 Invariant Validation Tiers\n\n`vault check` executes three validation tiers:\n- **Fast Tier (<1s)**: Schema validation, unique ID registry check, path lowercase conventions, required fields.\n- **Structural Tier (<10s)**: Cross-references between taxonomy, topics, chains, 3-part `common_mistake` markers (`**The Pitfall:**`, `**The Rationale:**`, `**The Consequence:**`), `napkin_math` structure, and visual asset existence.\n- **Slow Tier**: Link-rot checks across external documentation URLs and LLM math verification.\n\n---\n\n## 4. Pillar 3: Web Application Architecture (`app/`)\n\nThe frontend is built with **Next.js 16 (App Router)**, TypeScript, Tailwind CSS, KaTeX, and Framer Motion.\n\n```mermaid\ngraph LR\n    subgraph \"Data Access Layer (lib/corpus.ts)\"\n        CONFIG{\"vault-config.ts<br/>(static vs worker)\"}\n        LOCAL[\"Fetch /data/corpus.json<br/>(Static Bundle)\"]\n        REMOTE[\"Fetch Cloudflare Worker API<br/>(D1 Queries)\"]\n        CONFIG -->|Static Mode| LOCAL\n        CONFIG -->|Worker Mode| REMOTE\n    end\n\n    subgraph \"Interactive Modules\"\n        SR[\"Spaced Repetition<br/>(lib/progress.ts)\"]\n        ROOF[\"Roofline Engine<br/>(lib/hardware.ts)\"]\n        SIM[\"3D Sim Engine<br/>(lib/simulator.ts)\"]\n        COND[\"AI Conductor<br/>(lib/interview-conductor.ts)\"]\n    end\n\n    LOCAL --> SR\n    REMOTE --> SR\n    SR --> ROOF\n    SR --> SIM\n    SR --> COND\n```\n\n### 4.1 Dual-Mode Runtime Architecture\n\nThe web application supports two runtime modes via `src/lib/vault-config.ts`:\n1. **Worker Mode (`worker`)**: Light initial page load. Fetches catalog metadata initially and retrieves heavy fields (`scenario`, `details.*`) lazily from the Cloudflare Worker API.\n2. **Static Mode (`static`)**: Fully offline-capable and zero-dependency. Bundles the compiled `corpus.json` in `public/data/` for standalone local deployment or static hosting.\n\n### 4.2 Spaced Repetition Engine (`lib/progress.ts`)\n\nStaffML implements an adapted SuperMemo SM-2 spaced repetition algorithm stored locally in browser `localStorage`:\n- **Interval Progression**: Successful recalls advance review intervals (1 day $\\rightarrow$ 3 days $\\rightarrow$ 7 days $\\rightarrow$ 14 days $\\rightarrow$ 30 days).\n- **Mistake Recycling**: Incorrect ratings reset the repetition interval to 1 day, surfacing the question in tomorrow's review queue.\n- **Privacy First**: All candidate progress, ratings, and custom study plans remain 100% browser-local without mandatory user accounts or telemetry tracking.\n\n### 4.3 Interactive Calculators & Simulators\n\n1. **Roofline Model Engine (`app/roofline/page.tsx`, `lib/hardware.ts`)**:\n   - Calculates arithmetic intensity $\\text{AI} = \\frac{\\text{FLOPs}}{\\text{Bytes}}$ against hardware peak compute ($T_{\\text{peak}}$) and memory bandwidth ($B_{\\text{mem}}$).\n   - Computes the hardware ridge point $I_{\\text{ridge}} = \\frac{T_{\\text{peak}}}{B_{\\text{mem}}}$.\n   - Plots operational points for standard workloads (BERT, ResNet, GPT-2, LLaMA-70B FP16/INT8).\n\n2. **Distributed Training Cluster Simulator (`app/simulator/page.tsx`, `lib/simulator.ts`)**:\n   - Models 3D parallelism: Tensor Parallelism (TP), Pipeline Parallelism (PP), Data Parallelism (DP), and ZeRO-1/2/3.\n   - Calculates per-GPU memory breakdown (Weights, Gradients, Optimizer States, Activation Memory).\n   - Computes Ring AllReduce communication latency across hierarchical networks (NVLink intra-node vs InfiniBand NDR inter-node).\n   - Computes Model FLOPs Utilization (MFU), cluster Mean Time Between Failures (MTBF), and end-to-end training durations.\n\n3. **Radial Sunburst Explorer (`app/explore/page.tsx`)**:\n   - Interactive SVG sunburst visualizer enabling drill-down across Track $\\rightarrow$ Competency Area $\\rightarrow$ Topic $\\rightarrow$ Question Level with search filtering.\n\n---\n\n## 5. Pillar 4: Socratic AI Conductor & Multi-Provider Relay\n\nThe live interview experience (`/interview`) pairs candidates with an AI Socratic interviewer powered by `staffml-vault-worker` and `lib/interview-conductor.ts`.\n\n```mermaid\nsequenceDiagram\n    autonumber\n    actor Candidate as Candidate\n    participant UI as Interview UI (app/interview)\n    participant Cond as Conductor Engine (lib/interview-conductor)\n    participant Worker as Cloudflare Edge Worker\n    participant LLM as LLM Provider Cascade\n\n    Candidate->>UI: Selects Track, Level & Duration (e.g. Cloud L4, 30 min)\n    UI->>Cond: Initializes session & selects entry Socratic Chain\n    Cond->>Worker: POST /interview/turn (System Prompt + Question Context + Transcript)\n    Worker->>LLM: Fallback cascade (Groq ➔ OpenAI ➔ Anthropic ➔ Gemini ➔ Workers AI)\n    LLM-->>Worker: Streaming Response + Structured ---CONDUCTOR_META---\n    Worker-->>UI: Relays SSE stream\n    UI->>Candidate: Renders Socratic response\n    Candidate->>UI: Submits napkin math & architectural answer\n    UI->>Cond: Evaluates answer, adjusts depth, or traverses chain\n    Cond->>Worker: Next turn with rubric feedback criteria\n```\n\n### 5.1 Multi-Provider Fallback Cascade\n\nTo ensure 99.99% uptime and low latency for live mock interviews, the Cloudflare Worker relays requests through a prioritized multi-provider cascade:\n1. **Groq** (`llama-3.3-70b-versatile` / `mixtral-8x7b`): Ultra-low time-to-first-token (<200ms).\n2. **OpenAI** (`gpt-4o` / `gpt-4o-mini`): High-accuracy reasoning fallback.\n3. **Anthropic** (`claude-3-5-sonnet` / `claude-3-5-haiku`): Deep architectural critique.\n4. **Google Gemini** (`gemini-2.0-flash` / `gemini-1.5-pro`): Large context window fallback.\n5. **OpenRouter**: Global dynamic routing fallback.\n6. **Cloudflare Workers AI**: Edge-native, zero-external-dependency final fallback.\n\n### 5.2 Conductor Metadata Protocol\n\nAt each Socratic turn, the AI interviewer appends structured metadata:\n```\n---CONDUCTOR_META---\n{\n  \"intent\": \"probe\",\n  \"score\": 75,\n  \"napkin_math_correct\": true,\n  \"concept_tested\": \"PagedAttention KV cache allocation\",\n  \"advance_chain\": false\n}\n```\n`interview-conductor.ts` parses this block to dynamically decide whether to probe deeper, provide hints, retreat to foundational concepts, or advance to the next question in the chain.\n\n---\n\n## 6. Directory Map\n\n| Path | Purpose |\n| :--- | :--- |\n| **`staffml/vault/`** | The question corpus source of truth: 10,711 YAML files, `chains.json`, `taxonomy.yaml`, `id-registry.yaml`. |\n| **`staffml/vault/schema/`** | LinkML v1.0 schema definitions (`question_schema.yaml`, `enums.py`). |\n| **`staffml/vault/visuals/`** | 144 source SVG architectural and memory diagrams. |\n| **`staffml/vault-cli/`** | Python CLI toolchain (`vault` command) for authoring, invariant checking, building, and publishing. |\n| **`staffml/app/`** | Next.js 16 App Router web application (`src/app/`, `src/components/`, `src/lib/`). |\n| **`staffml/app/worker/`** | Next.js serverless worker relay for LLM conductor streaming. |\n| **`staffml/vault-worker/`** | Cloudflare Edge Worker serving D1 database endpoints and search. |\n| **`staffml/paper/`** | Academic publication macros and LaTeX build scripts synchronized with `vault.db`. |\n\n---\n\n## 7. Verification & Build Contract\n\nTo verify the entire software stack locally:\n\n```bash\n# 1. Verify Vault corpus invariants & health\ncd staffml/vault-cli\npython3 -m pytest -o addopts=\"\" tests/\npython3 -m vault_cli.main check\npython3 -m vault_cli.main doctor\n\n# 2. Compile local corpus and database\npython3 -m vault_cli.main build --local\n\n# 3. Test & build Next.js application\ncd ../staffml\nnpm test\nNEXT_PUBLIC_VAULT_FALLBACK=static npm run build\n\n# 4. Test Cloudflare Edge Worker\ncd ../vault-worker\nnpm test\n```\n","isInternal":false,"tokens":3757,"sizeBytes":14794},{"name":"accepted_fps_notation.json","path":"binder/tools/audit/accepted_fps_notation.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/accepted_fps_notation.json","title":"Audit Skill","category":"anthropic-skill","format":"json","content":"{\n  \"schema_version\": 1,\n  \"description\": \"Persistent accept-list for notation-consistency scanner false positives / intentional exceptions.\",\n  \"entries\": []\n}\n","frontmatter":{"schema_version":1,"description":"Persistent accept-list for notation-consistency scanner false positives / intentional exceptions.","entries":[]},"isInternal":false,"tokens":34,"sizeBytes":161},{"name":"accepted_fps.json","path":"binder/tools/audit/accepted_fps.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/accepted_fps.json","title":"Audit Skill","category":"anthropic-skill","format":"json","content":"{\n  \"schema_version\": 1,\n  \"description\": \"Persistent accept-list of editorially reviewed scanner exceptions. The PR 2094 entries preserve Zeljko Godler-approved Volume I pagination: matching is by category, repository-relative file, and exact source line, so any edited line or new violation returns to the open gate.\",\n  \"entries\": []\n}\n","frontmatter":{"schema_version":1,"description":"Persistent accept-list of editorially reviewed scanner exceptions. The PR 2094 entries preserve Zeljko Godler-approved Volume I pagination: matching is by category, repository-relative file, and exact source line, so any edited line or new violation returns to the open gate.","entries":[]},"isInternal":false,"tokens":75,"sizeBytes":339},{"name":"dead_constants_verified.json","path":"binder/tools/audit/artifacts/dead_constants_verified.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/artifacts/dead_constants_verified.json","title":"Artifacts Skill","category":"anthropic-skill","format":"json","content":"# Artifacts Skill\n\nPath: `binder/tools/audit/artifacts/dead_constants_verified.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/artifacts/dead_constants_verified.json)","tokens":300,"sizeBytes":237},{"name":"fmt_design_b_inventory.json","path":"binder/tools/audit/artifacts/fmt_design_b_inventory.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/artifacts/fmt_design_b_inventory.json","title":"Artifacts Skill","category":"anthropic-skill","format":"json","content":"# Artifacts Skill\n\nPath: `binder/tools/audit/artifacts/fmt_design_b_inventory.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/artifacts/fmt_design_b_inventory.json)","tokens":300,"sizeBytes":235},{"name":"registry_migration_manifest.json","path":"binder/tools/audit/artifacts/registry_migration_manifest.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/artifacts/registry_migration_manifest.json","title":"Artifacts Skill","category":"anthropic-skill","format":"json","content":"# Artifacts Skill\n\nPath: `binder/tools/audit/artifacts/registry_migration_manifest.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/artifacts/registry_migration_manifest.json)","tokens":300,"sizeBytes":245},{"name":"captions_baseline.json","path":"binder/tools/audit/baselines/captions_baseline.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/baselines/captions_baseline.json","title":"Baselines Skill","category":"anthropic-skill","format":"json","content":"# Baselines Skill\n\nPath: `binder/tools/audit/baselines/captions_baseline.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/baselines/captions_baseline.json)","tokens":300,"sizeBytes":225},{"name":"scaffold_citation_baseline.json","path":"binder/tools/audit/baselines/scaffold_citation_baseline.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/baselines/scaffold_citation_baseline.json","title":"Baselines Skill","category":"anthropic-skill","format":"json","content":"# Baselines Skill\n\nPath: `binder/tools/audit/baselines/scaffold_citation_baseline.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/baselines/scaffold_citation_baseline.json)","tokens":300,"sizeBytes":243},{"name":"global_backmatter_references.json","path":"binder/tools/audit/data/chapter_terms/global_backmatter_references.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_backmatter_references.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_backmatter_references.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_backmatter_references.json)","tokens":300,"sizeBytes":269},{"name":"global_backmatter_resources_phd_survival_guide.json","path":"binder/tools/audit/data/chapter_terms/global_backmatter_resources_phd_survival_guide.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_backmatter_resources_phd_survival_guide.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_backmatter_resources_phd_survival_guide.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_backmatter_resources_phd_survival_guide.json)","tokens":300,"sizeBytes":305},{"name":"global_frontmatter_about_about.json","path":"binder/tools/audit/data/chapter_terms/global_frontmatter_about_about.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_frontmatter_about_about.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_frontmatter_about_about.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_frontmatter_about_about.json)","tokens":300,"sizeBytes":273},{"name":"global_frontmatter_acknowledgements_acknowledgements.json","path":"binder/tools/audit/data/chapter_terms/global_frontmatter_acknowledgements_acknowledgements.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_frontmatter_acknowledgements_acknowledgements.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_frontmatter_acknowledgements_acknowledgements.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_frontmatter_acknowledgements_acknowledgements.json)","tokens":300,"sizeBytes":317},{"name":"global_frontmatter_index.json","path":"binder/tools/audit/data/chapter_terms/global_frontmatter_index.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_frontmatter_index.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_frontmatter_index.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_frontmatter_index.json)","tokens":300,"sizeBytes":261},{"name":"global_frontmatter_socratiq_socratiq.json","path":"binder/tools/audit/data/chapter_terms/global_frontmatter_socratiq_socratiq.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_frontmatter_socratiq_socratiq.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_frontmatter_socratiq_socratiq.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_frontmatter_socratiq_socratiq.json)","tokens":300,"sizeBytes":285},{"name":"vol1_backmatter_appendix_algorithm.json","path":"binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_algorithm.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_algorithm.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_algorithm.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_algorithm.json)","tokens":300,"sizeBytes":281},{"name":"vol1_backmatter_appendix_assumptions.json","path":"binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_assumptions.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_assumptions.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_assumptions.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_assumptions.json)","tokens":300,"sizeBytes":285},{"name":"vol1_backmatter_appendix_dam.json","path":"binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_dam.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_dam.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_dam.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_dam.json)","tokens":300,"sizeBytes":269},{"name":"vol1_backmatter_appendix_data.json","path":"binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_data.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_data.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_data.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_data.json)","tokens":300,"sizeBytes":271},{"name":"vol1_backmatter_appendix_machine.json","path":"binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_machine.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_machine.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_machine.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_machine.json)","tokens":300,"sizeBytes":277},{"name":"vol1_backmatter_glossary_glossary.json","path":"binder/tools/audit/data/chapter_terms/vol1_backmatter_glossary_glossary.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_glossary_glossary.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_glossary_glossary.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_glossary_glossary.json)","tokens":300,"sizeBytes":279},{"name":"vol1_backmatter_references.json","path":"binder/tools/audit/data/chapter_terms/vol1_backmatter_references.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_references.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_references.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_references.json)","tokens":300,"sizeBytes":265},{"name":"vol1_benchmarking_benchmarking.json","path":"binder/tools/audit/data/chapter_terms/vol1_benchmarking_benchmarking.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_benchmarking_benchmarking.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_benchmarking_benchmarking.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_benchmarking_benchmarking.json)","tokens":300,"sizeBytes":273},{"name":"vol1_conclusion_conclusion.json","path":"binder/tools/audit/data/chapter_terms/vol1_conclusion_conclusion.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_conclusion_conclusion.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_conclusion_conclusion.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_conclusion_conclusion.json)","tokens":300,"sizeBytes":265},{"name":"vol1_data_engineering_data_engineering.json","path":"binder/tools/audit/data/chapter_terms/vol1_data_engineering_data_engineering.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_data_engineering_data_engineering.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_data_engineering_data_engineering.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_data_engineering_data_engineering.json)","tokens":300,"sizeBytes":289},{"name":"vol1_data_selection_data_selection.json","path":"binder/tools/audit/data/chapter_terms/vol1_data_selection_data_selection.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_data_selection_data_selection.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_data_selection_data_selection.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_data_selection_data_selection.json)","tokens":300,"sizeBytes":281},{"name":"vol1_frameworks_frameworks.json","path":"binder/tools/audit/data/chapter_terms/vol1_frameworks_frameworks.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frameworks_frameworks.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frameworks_frameworks.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frameworks_frameworks.json)","tokens":300,"sizeBytes":265},{"name":"vol1_frontmatter__conventions.json","path":"binder/tools/audit/data/chapter_terms/vol1_frontmatter__conventions.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter__conventions.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter__conventions.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter__conventions.json)","tokens":300,"sizeBytes":271},{"name":"vol1_frontmatter__notation_body.json","path":"binder/tools/audit/data/chapter_terms/vol1_frontmatter__notation_body.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter__notation_body.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter__notation_body.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter__notation_body.json)","tokens":300,"sizeBytes":275},{"name":"vol1_frontmatter_about.json","path":"binder/tools/audit/data/chapter_terms/vol1_frontmatter_about.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_about.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_about.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_about.json)","tokens":300,"sizeBytes":257},{"name":"vol1_frontmatter_acknowledgements.json","path":"binder/tools/audit/data/chapter_terms/vol1_frontmatter_acknowledgements.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_acknowledgements.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_acknowledgements.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_acknowledgements.json)","tokens":300,"sizeBytes":279},{"name":"vol1_frontmatter_ai_use.json","path":"binder/tools/audit/data/chapter_terms/vol1_frontmatter_ai_use.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_ai_use.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_ai_use.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_ai_use.json)","tokens":300,"sizeBytes":259},{"name":"vol1_frontmatter_author_note.json","path":"binder/tools/audit/data/chapter_terms/vol1_frontmatter_author_note.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_author_note.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_author_note.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_author_note.json)","tokens":300,"sizeBytes":269},{"name":"vol1_frontmatter_dedication.json","path":"binder/tools/audit/data/chapter_terms/vol1_frontmatter_dedication.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_dedication.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_dedication.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_dedication.json)","tokens":300,"sizeBytes":267},{"name":"vol1_frontmatter_foreword.json","path":"binder/tools/audit/data/chapter_terms/vol1_frontmatter_foreword.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_foreword.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_foreword.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_foreword.json)","tokens":300,"sizeBytes":263},{"name":"vol1_frontmatter_notation.json","path":"binder/tools/audit/data/chapter_terms/vol1_frontmatter_notation.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_notation.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_notation.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_notation.json)","tokens":300,"sizeBytes":263},{"name":"vol1_hw_acceleration_hw_acceleration.json","path":"binder/tools/audit/data/chapter_terms/vol1_hw_acceleration_hw_acceleration.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_hw_acceleration_hw_acceleration.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_hw_acceleration_hw_acceleration.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_hw_acceleration_hw_acceleration.json)","tokens":300,"sizeBytes":285},{"name":"vol1_index.json","path":"binder/tools/audit/data/chapter_terms/vol1_index.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_index.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_index.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_index.json)","tokens":300,"sizeBytes":233},{"name":"vol1_introduction_introduction.json","path":"binder/tools/audit/data/chapter_terms/vol1_introduction_introduction.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_introduction_introduction.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_introduction_introduction.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_introduction_introduction.json)","tokens":300,"sizeBytes":273},{"name":"vol1_ml_lifecycle_ml_lifecycle.json","path":"binder/tools/audit/data/chapter_terms/vol1_ml_lifecycle_ml_lifecycle.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_ml_lifecycle_ml_lifecycle.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_ml_lifecycle_ml_lifecycle.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_ml_lifecycle_ml_lifecycle.json)","tokens":300,"sizeBytes":273},{"name":"vol1_ml_ops_ml_ops.json","path":"binder/tools/audit/data/chapter_terms/vol1_ml_ops_ml_ops.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_ml_ops_ml_ops.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_ml_ops_ml_ops.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_ml_ops_ml_ops.json)","tokens":300,"sizeBytes":249},{"name":"vol1_model_compression_model_compression.json","path":"binder/tools/audit/data/chapter_terms/vol1_model_compression_model_compression.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_model_compression_model_compression.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_model_compression_model_compression.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_model_compression_model_compression.json)","tokens":300,"sizeBytes":293},{"name":"vol1_model_serving_model_serving.json","path":"binder/tools/audit/data/chapter_terms/vol1_model_serving_model_serving.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_model_serving_model_serving.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_model_serving_model_serving.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_model_serving_model_serving.json)","tokens":300,"sizeBytes":277},{"name":"vol1_nn_architectures_nn_architectures.json","path":"binder/tools/audit/data/chapter_terms/vol1_nn_architectures_nn_architectures.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_nn_architectures_nn_architectures.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_nn_architectures_nn_architectures.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_nn_architectures_nn_architectures.json)","tokens":300,"sizeBytes":289},{"name":"vol1_nn_computation_nn_computation.json","path":"binder/tools/audit/data/chapter_terms/vol1_nn_computation_nn_computation.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_nn_computation_nn_computation.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_nn_computation_nn_computation.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_nn_computation_nn_computation.json)","tokens":300,"sizeBytes":281},{"name":"vol1_parts_build_principles.json","path":"binder/tools/audit/data/chapter_terms/vol1_parts_build_principles.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_parts_build_principles.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_parts_build_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_parts_build_principles.json)","tokens":300,"sizeBytes":267},{"name":"vol1_parts_deploy_principles.json","path":"binder/tools/audit/data/chapter_terms/vol1_parts_deploy_principles.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_parts_deploy_principles.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_parts_deploy_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_parts_deploy_principles.json)","tokens":300,"sizeBytes":269},{"name":"vol1_parts_foundations_principles.json","path":"binder/tools/audit/data/chapter_terms/vol1_parts_foundations_principles.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_parts_foundations_principles.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_parts_foundations_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_parts_foundations_principles.json)","tokens":300,"sizeBytes":279},{"name":"vol1_parts_optimize_principles.json","path":"binder/tools/audit/data/chapter_terms/vol1_parts_optimize_principles.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_parts_optimize_principles.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_parts_optimize_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_parts_optimize_principles.json)","tokens":300,"sizeBytes":273},{"name":"vol1_responsible_engr_responsible_engr.json","path":"binder/tools/audit/data/chapter_terms/vol1_responsible_engr_responsible_engr.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_responsible_engr_responsible_engr.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_responsible_engr_responsible_engr.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_responsible_engr_responsible_engr.json)","tokens":300,"sizeBytes":289},{"name":"vol1_system_paradigms_system_paradigms.json","path":"binder/tools/audit/data/chapter_terms/vol1_system_paradigms_system_paradigms.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_system_paradigms_system_paradigms.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_system_paradigms_system_paradigms.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_system_paradigms_system_paradigms.json)","tokens":300,"sizeBytes":289},{"name":"vol1_training_training.json","path":"binder/tools/audit/data/chapter_terms/vol1_training_training.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_training_training.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_training_training.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_training_training.json)","tokens":300,"sizeBytes":257},{"name":"vol2_backmatter_appendix_assumptions.json","path":"binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_assumptions.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_assumptions.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_assumptions.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_assumptions.json)","tokens":300,"sizeBytes":285},{"name":"vol2_backmatter_appendix_c3.json","path":"binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_c3.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_c3.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_c3.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_c3.json)","tokens":300,"sizeBytes":267},{"name":"vol2_backmatter_appendix_communication.json","path":"binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_communication.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_communication.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_communication.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_communication.json)","tokens":300,"sizeBytes":289},{"name":"vol2_backmatter_appendix_dam.json","path":"binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_dam.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_dam.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_dam.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_dam.json)","tokens":300,"sizeBytes":269},{"name":"vol2_backmatter_appendix_fleet.json","path":"binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_fleet.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_fleet.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_fleet.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_fleet.json)","tokens":300,"sizeBytes":273},{"name":"vol2_backmatter_appendix_inference.json","path":"binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_inference.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_inference.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_inference.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_inference.json)","tokens":300,"sizeBytes":281},{"name":"vol2_backmatter_appendix_reliability.json","path":"binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_reliability.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_reliability.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_reliability.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_appendix_reliability.json)","tokens":300,"sizeBytes":285},{"name":"vol2_backmatter_glossary_glossary.json","path":"binder/tools/audit/data/chapter_terms/vol2_backmatter_glossary_glossary.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_glossary_glossary.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_glossary_glossary.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_glossary_glossary.json)","tokens":300,"sizeBytes":279},{"name":"vol2_backmatter_references.json","path":"binder/tools/audit/data/chapter_terms/vol2_backmatter_references.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_references.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_backmatter_references.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_backmatter_references.json)","tokens":300,"sizeBytes":265},{"name":"vol2_collective_communication_collective_communication.json","path":"binder/tools/audit/data/chapter_terms/vol2_collective_communication_collective_communication.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_collective_communication_collective_communication.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_collective_communication_collective_communication.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_collective_communication_collective_communication.json)","tokens":300,"sizeBytes":321},{"name":"vol2_compute_infrastructure_compute_infrastructure.json","path":"binder/tools/audit/data/chapter_terms/vol2_compute_infrastructure_compute_infrastructure.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_compute_infrastructure_compute_infrastructure.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_compute_infrastructure_compute_infrastructure.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_compute_infrastructure_compute_infrastructure.json)","tokens":300,"sizeBytes":313},{"name":"vol2_conclusion_conclusion.json","path":"binder/tools/audit/data/chapter_terms/vol2_conclusion_conclusion.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_conclusion_conclusion.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_conclusion_conclusion.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_conclusion_conclusion.json)","tokens":300,"sizeBytes":265},{"name":"vol2_data_storage_data_storage.json","path":"binder/tools/audit/data/chapter_terms/vol2_data_storage_data_storage.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_data_storage_data_storage.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_data_storage_data_storage.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_data_storage_data_storage.json)","tokens":300,"sizeBytes":273},{"name":"vol2_distributed_training_distributed_training.json","path":"binder/tools/audit/data/chapter_terms/vol2_distributed_training_distributed_training.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_distributed_training_distributed_training.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_distributed_training_distributed_training.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_distributed_training_distributed_training.json)","tokens":300,"sizeBytes":305},{"name":"vol2_edge_intelligence_edge_intelligence.json","path":"binder/tools/audit/data/chapter_terms/vol2_edge_intelligence_edge_intelligence.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_edge_intelligence_edge_intelligence.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_edge_intelligence_edge_intelligence.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_edge_intelligence_edge_intelligence.json)","tokens":300,"sizeBytes":293},{"name":"vol2_fault_tolerance_fault_tolerance.json","path":"binder/tools/audit/data/chapter_terms/vol2_fault_tolerance_fault_tolerance.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_fault_tolerance_fault_tolerance.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_fault_tolerance_fault_tolerance.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_fault_tolerance_fault_tolerance.json)","tokens":300,"sizeBytes":285},{"name":"vol2_fleet_orchestration_fleet_orchestration.json","path":"binder/tools/audit/data/chapter_terms/vol2_fleet_orchestration_fleet_orchestration.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_fleet_orchestration_fleet_orchestration.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_fleet_orchestration_fleet_orchestration.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_fleet_orchestration_fleet_orchestration.json)","tokens":300,"sizeBytes":301},{"name":"vol2_frontmatter__notation_scaling.json","path":"binder/tools/audit/data/chapter_terms/vol2_frontmatter__notation_scaling.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter__notation_scaling.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter__notation_scaling.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter__notation_scaling.json)","tokens":300,"sizeBytes":281},{"name":"vol2_frontmatter_about.json","path":"binder/tools/audit/data/chapter_terms/vol2_frontmatter_about.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_about.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_about.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_about.json)","tokens":300,"sizeBytes":257},{"name":"vol2_frontmatter_acknowledgements.json","path":"binder/tools/audit/data/chapter_terms/vol2_frontmatter_acknowledgements.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_acknowledgements.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_acknowledgements.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_acknowledgements.json)","tokens":300,"sizeBytes":279},{"name":"vol2_frontmatter_ai_use.json","path":"binder/tools/audit/data/chapter_terms/vol2_frontmatter_ai_use.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_ai_use.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_ai_use.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_ai_use.json)","tokens":300,"sizeBytes":259},{"name":"vol2_frontmatter_author_note.json","path":"binder/tools/audit/data/chapter_terms/vol2_frontmatter_author_note.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_author_note.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_author_note.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_author_note.json)","tokens":300,"sizeBytes":269},{"name":"vol2_frontmatter_dedication.json","path":"binder/tools/audit/data/chapter_terms/vol2_frontmatter_dedication.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_dedication.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_dedication.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_dedication.json)","tokens":300,"sizeBytes":267},{"name":"vol2_frontmatter_foreword.json","path":"binder/tools/audit/data/chapter_terms/vol2_frontmatter_foreword.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_foreword.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_foreword.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_foreword.json)","tokens":300,"sizeBytes":263},{"name":"vol2_frontmatter_notation.json","path":"binder/tools/audit/data/chapter_terms/vol2_frontmatter_notation.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_notation.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_frontmatter_notation.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_frontmatter_notation.json)","tokens":300,"sizeBytes":263},{"name":"vol2_index.json","path":"binder/tools/audit/data/chapter_terms/vol2_index.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_index.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_index.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_index.json)","tokens":300,"sizeBytes":233},{"name":"vol2_inference_inference.json","path":"binder/tools/audit/data/chapter_terms/vol2_inference_inference.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_inference_inference.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_inference_inference.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_inference_inference.json)","tokens":300,"sizeBytes":261},{"name":"vol2_introduction_introduction.json","path":"binder/tools/audit/data/chapter_terms/vol2_introduction_introduction.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_introduction_introduction.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_introduction_introduction.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_introduction_introduction.json)","tokens":300,"sizeBytes":273},{"name":"vol2_network_fabrics_network_fabrics.json","path":"binder/tools/audit/data/chapter_terms/vol2_network_fabrics_network_fabrics.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_network_fabrics_network_fabrics.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_network_fabrics_network_fabrics.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_network_fabrics_network_fabrics.json)","tokens":300,"sizeBytes":285},{"name":"vol2_ops_scale_ops_scale.json","path":"binder/tools/audit/data/chapter_terms/vol2_ops_scale_ops_scale.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_ops_scale_ops_scale.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_ops_scale_ops_scale.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_ops_scale_ops_scale.json)","tokens":300,"sizeBytes":261},{"name":"vol2_parts_deployment_principles.json","path":"binder/tools/audit/data/chapter_terms/vol2_parts_deployment_principles.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_parts_deployment_principles.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_parts_deployment_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_parts_deployment_principles.json)","tokens":300,"sizeBytes":277},{"name":"vol2_parts_distributed_ml_principles.json","path":"binder/tools/audit/data/chapter_terms/vol2_parts_distributed_ml_principles.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_parts_distributed_ml_principles.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_parts_distributed_ml_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_parts_distributed_ml_principles.json)","tokens":300,"sizeBytes":285},{"name":"vol2_parts_fleet_principles.json","path":"binder/tools/audit/data/chapter_terms/vol2_parts_fleet_principles.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_parts_fleet_principles.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_parts_fleet_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_parts_fleet_principles.json)","tokens":300,"sizeBytes":267},{"name":"vol2_parts_responsible_fleet_principles.json","path":"binder/tools/audit/data/chapter_terms/vol2_parts_responsible_fleet_principles.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_parts_responsible_fleet_principles.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_parts_responsible_fleet_principles.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_parts_responsible_fleet_principles.json)","tokens":300,"sizeBytes":291},{"name":"vol2_performance_engineering_performance_engineering.json","path":"binder/tools/audit/data/chapter_terms/vol2_performance_engineering_performance_engineering.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_performance_engineering_performance_engineering.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_performance_engineering_performance_engineering.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_performance_engineering_performance_engineering.json)","tokens":300,"sizeBytes":317},{"name":"vol2_responsible_ai_responsible_ai.json","path":"binder/tools/audit/data/chapter_terms/vol2_responsible_ai_responsible_ai.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_responsible_ai_responsible_ai.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_responsible_ai_responsible_ai.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_responsible_ai_responsible_ai.json)","tokens":300,"sizeBytes":281},{"name":"vol2_robust_ai_robust_ai.json","path":"binder/tools/audit/data/chapter_terms/vol2_robust_ai_robust_ai.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_robust_ai_robust_ai.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_robust_ai_robust_ai.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_robust_ai_robust_ai.json)","tokens":300,"sizeBytes":261},{"name":"vol2_security_privacy_security_privacy.json","path":"binder/tools/audit/data/chapter_terms/vol2_security_privacy_security_privacy.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_security_privacy_security_privacy.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_security_privacy_security_privacy.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_security_privacy_security_privacy.json)","tokens":300,"sizeBytes":289},{"name":"vol2_sustainable_ai_sustainable_ai.json","path":"binder/tools/audit/data/chapter_terms/vol2_sustainable_ai_sustainable_ai.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_sustainable_ai_sustainable_ai.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol2_sustainable_ai_sustainable_ai.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol2_sustainable_ai_sustainable_ai.json)","tokens":300,"sizeBytes":281},{"name":"vol3_index.json","path":"binder/tools/audit/data/chapter_terms/vol3_index.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol3_index.json","title":"Chapter_terms Skill","category":"anthropic-skill","format":"json","content":"# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol3_index.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol3_index.json)","tokens":300,"sizeBytes":233},{"name":"notation_strict_baseline.json","path":"binder/tools/audit/data/notation_strict_baseline.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/notation_strict_baseline.json","title":"Data Skill","category":"anthropic-skill","format":"json","content":"# Data Skill\n\nPath: `binder/tools/audit/data/notation_strict_baseline.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/notation_strict_baseline.json)","tokens":300,"sizeBytes":224},{"name":"terms_registry.json","path":"binder/tools/audit/data/terms_registry.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/terms_registry.json","title":"Data Skill","category":"anthropic-skill","format":"json","content":"# Data Skill\n\nPath: `binder/tools/audit/data/terms_registry.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/terms_registry.json)","tokens":300,"sizeBytes":204},{"name":"terms_registry.yaml","path":"binder/tools/audit/data/terms_registry.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/terms_registry.yaml","title":"Data Skill","category":"anthropic-skill","format":"yaml","content":"# Data Skill\n\nPath: `binder/tools/audit/data/terms_registry.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/terms_registry.yaml)","tokens":300,"sizeBytes":204},{"name":"epubcheck-baseline.json","path":"binder/tools/audit/epubcheck-baseline.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/epubcheck-baseline.json","title":"Audit Skill","category":"anthropic-skill","format":"json","content":"{\n  \"generated_at\": \"2026-04-20T20:24:28+00:00\",\n  \"generated_by\": \"binder check epub --scope epubcheck --update-baseline\",\n  \"description\": \"Max allowed per-volume epubcheck counts. `./binder/binder check epub --scope epubcheck --baseline <this>` fails only if any current count exceeds the recorded value. Run `--update-baseline` again after a cleanup to lower the ceiling.\",\n  \"volumes\": {\n    \"vol1\": {\n      \"FATAL\": 0,\n      \"ERROR\": 0,\n      \"WARNING\": 0\n    },\n    \"vol2\": {\n      \"FATAL\": 0,\n      \"ERROR\": 0,\n      \"WARNING\": 0\n    }\n  }\n}\n","frontmatter":{"generated_at":"2026-04-20T20:24:28+00:00","generated_by":"binder check epub --scope epubcheck --update-baseline","description":"Max allowed per-volume epubcheck counts. `./binder/binder check epub --scope epubcheck --baseline <this>` fails only if any current count exceeds the recorded value. Run `--update-baseline` again after a cleanup to lower the ceiling.","volumes":{"vol1":{"FATAL":0,"ERROR":0,"WARNING":0},"vol2":{"FATAL":0,"ERROR":0,"WARNING":0}}},"isInternal":false,"tokens":169,"sizeBytes":550},{"name":"lego_units_baseline.json","path":"binder/tools/audit/lego_units_baseline.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/lego_units_baseline.json","title":"Audit Skill","category":"anthropic-skill","format":"json","content":"[\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/backmatter/appendix_algorithm.qmd\",\n    \"line\": 416,\n    \"message\": \"Closed name act_small_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/backmatter/appendix_machine.qmd\",\n    \"line\": 783,\n    \"message\": \"Closed name w_latency_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/backmatter/appendix_machine.qmd\",\n    \"line\": 1129,\n    \"message\": \"Closed name large_data_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/benchmarking/benchmarking.qmd\",\n    \"line\": 1725,\n    \"message\": \"Closed name latency_fp32_ms_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/benchmarking/benchmarking.qmd\",\n    \"line\": 1726,\n    \"message\": \"Closed name latency_int8_ms_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/benchmarking/benchmarking.qmd\",\n    \"line\": 2529,\n    \"message\": \"Closed name e_fp32_load_mj_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/benchmarking/benchmarking.qmd\",\n    \"line\": 2530,\n    \"message\": \"Closed name e_fp32_compute_mj_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/hw_acceleration/hw_acceleration.qmd\",\n    \"line\": 288,\n    \"message\": \"Closed name p_resnet_per_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/hw_acceleration/hw_acceleration.qmd\",\n    \"line\": 296,\n    \"message\": \"Closed name p_gpt2_per_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/hw_acceleration/hw_acceleration.qmd\",\n    \"line\": 1550,\n    \"message\": \"Closed name scalar_ms_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/nn_architectures/nn_architectures.qmd\",\n    \"line\": 594,\n    \"message\": \"Closed name gpt3_fp16_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/nn_architectures/nn_architectures.qmd\",\n    \"line\": 5146,\n    \"message\": \"Closed name target_latency_ms_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/nn_architectures/nn_architectures.qmd\",\n    \"line\": 5147,\n    \"message\": \"Closed name compute_latency_ms_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/nn_architectures/nn_architectures.qmd\",\n    \"line\": 5150,\n    \"message\": \"Closed name energy_mj_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/nn_architectures/nn_architectures.qmd\",\n    \"line\": 5151,\n    \"message\": \"Closed name energy_j_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/nn_computation/nn_computation.qmd\",\n    \"line\": 2147,\n    \"message\": \"Closed name tpuv1_tdp_w_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/nn_computation/nn_computation.qmd\",\n    \"line\": 4974,\n    \"message\": \"Closed name a100_tdp_w_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/nn_computation/nn_computation.qmd\",\n    \"line\": 4975,\n    \"message\": \"Closed name h100_tdp_w_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/nn_computation/nn_computation.qmd\",\n    \"line\": 4978,\n    \"message\": \"Closed name edge_tpu_tdp_w_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/nn_computation/nn_computation.qmd\",\n    \"line\": 4980,\n    \"message\": \"Closed name jetson_orin_tdp_low_w_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/nn_computation/nn_computation.qmd\",\n    \"line\": 4981,\n    \"message\": \"Closed name jetson_orin_tdp_high_w_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/nn_computation/nn_computation.qmd\",\n    \"line\": 5616,\n    \"message\": \"Closed name old_power_low_w_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/nn_computation/nn_computation.qmd\",\n    \"line\": 5617,\n    \"message\": \"Closed name old_power_high_w_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/nn_computation/nn_computation.qmd\",\n    \"line\": 5618,\n    \"message\": \"Closed name modern_power_w_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/nn_computation/nn_computation.qmd\",\n    \"line\": 5621,\n    \"message\": \"Closed name old_energy_per_inference_j_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/nn_computation/nn_computation.qmd\",\n    \"line\": 5622,\n    \"message\": \"Closed name modern_energy_per_inference_mj_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/responsible_engr/responsible_engr.qmd\",\n    \"line\": 2155,\n    \"message\": \"Closed name carbon_intensity_g_kwh_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/responsible_engr/responsible_engr.qmd\",\n    \"line\": 2157,\n    \"message\": \"Closed name total_emissions_kg_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/training/training.qmd\",\n    \"line\": 2821,\n    \"message\": \"Closed name layer_dim_w_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/training/training.qmd\",\n    \"line\": 2827,\n    \"message\": \"Closed name conv_w_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/training/training.qmd\",\n    \"line\": 3114,\n    \"message\": \"Closed name resnet_conv1_w_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol1/training/training.qmd\",\n    \"line\": 5705,\n    \"message\": \"Closed name grid_kg_kwh_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/backmatter/appendix_assumptions.qmd\",\n    \"line\": 145,\n    \"message\": \"Closed name tdp_w_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/backmatter/appendix_assumptions.qmd\",\n    \"line\": 342,\n    \"message\": \"Closed name recovery_checkpoint_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/backmatter/appendix_assumptions.qmd\",\n    \"line\": 343,\n    \"message\": \"Closed name recovery_time_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/backmatter/appendix_assumptions.qmd\",\n    \"line\": 467,\n    \"message\": \"Closed name tenk_h100_it_mw_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/backmatter/appendix_assumptions.qmd\",\n    \"line\": 468,\n    \"message\": \"Closed name pue_extra_overhead_mw_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/backmatter/appendix_fleet.qmd\",\n    \"line\": 412,\n    \"message\": \"Closed name write_70b_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/backmatter/appendix_fleet.qmd\",\n    \"line\": 413,\n    \"message\": \"Closed name write_175b_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/backmatter/appendix_inference.qmd\",\n    \"line\": 287,\n    \"message\": \"Closed name expected_total_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/backmatter/appendix_reliability.qmd\",\n    \"line\": 559,\n    \"message\": \"Closed name _ckpt_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/compute_infrastructure/compute_infrastructure.qmd\",\n    \"line\": 1467,\n    \"message\": \"Closed name inf_weight_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/compute_infrastructure/compute_infrastructure.qmd\",\n    \"line\": 2690,\n    \"message\": \"Closed name weights_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/compute_infrastructure/compute_infrastructure.qmd\",\n    \"line\": 2691,\n    \"message\": \"Closed name gradients_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/compute_infrastructure/compute_infrastructure.qmd\",\n    \"line\": 2692,\n    \"message\": \"Closed name optimizer_m_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/compute_infrastructure/compute_infrastructure.qmd\",\n    \"line\": 2693,\n    \"message\": \"Closed name optimizer_v_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/compute_infrastructure/compute_infrastructure.qmd\",\n    \"line\": 3122,\n    \"message\": \"Closed name comm_phase_w_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/compute_infrastructure/compute_infrastructure.qmd\",\n    \"line\": 3123,\n    \"message\": \"Closed name power_delta_w_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/compute_infrastructure/compute_infrastructure.qmd\",\n    \"line\": 3775,\n    \"message\": \"Closed name mtbf_system_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/distributed_training/distributed_training.qmd\",\n    \"line\": 983,\n    \"message\": \"Closed name exposed_step_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/distributed_training/distributed_training.qmd\",\n    \"line\": 985,\n    \"message\": \"Closed name t_compute_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/edge_intelligence/edge_intelligence.qmd\",\n    \"line\": 1062,\n    \"message\": \"Closed name battery_power_w_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/fault_tolerance/fault_tolerance.qmd\",\n    \"line\": 1900,\n    \"message\": \"Closed name training_step_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/fault_tolerance/fault_tolerance.qmd\",\n    \"line\": 2111,\n    \"message\": \"Closed name gpt3_shard_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/fault_tolerance/fault_tolerance.qmd\",\n    \"line\": 2304,\n    \"message\": \"Closed name t_write_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/fault_tolerance/fault_tolerance.qmd\",\n    \"line\": 2306,\n    \"message\": \"Closed name mtbf_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/fault_tolerance/fault_tolerance.qmd\",\n    \"line\": 2307,\n    \"message\": \"Closed name tau_opt_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/fault_tolerance/fault_tolerance.qmd\",\n    \"line\": 2586,\n    \"message\": \"Closed name min_write_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/fault_tolerance/fault_tolerance.qmd\",\n    \"line\": 2591,\n    \"message\": \"Closed name gpu_cpu_parallel_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/fault_tolerance/fault_tolerance.qmd\",\n    \"line\": 2592,\n    \"message\": \"Closed name gpu_cpu_single_path_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/fault_tolerance/fault_tolerance.qmd\",\n    \"line\": 2884,\n    \"message\": \"Closed name t_detect_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/inference/inference.qmd\",\n    \"line\": 2453,\n    \"message\": \"Closed name kv_savings_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/inference/inference.qmd\",\n    \"line\": 3775,\n    \"message\": \"Closed name nvlink_ms_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/inference/inference.qmd\",\n    \"line\": 3776,\n    \"message\": \"Closed name ib_ms_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/inference/inference.qmd\",\n    \"line\": 3777,\n    \"message\": \"Closed name eth_ms_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/introduction/introduction.qmd\",\n    \"line\": 1695,\n    \"message\": \"Closed name sync_energy_j_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/introduction/introduction.qmd\",\n    \"line\": 1697,\n    \"message\": \"Closed name sync_energy_mj_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/ops_scale/ops_scale.qmd\",\n    \"line\": 3143,\n    \"message\": \"Closed name mtbf_system_s_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/performance_engineering/performance_engineering.qmd\",\n    \"line\": 704,\n    \"message\": \"Closed name weight_gb_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/performance_engineering/performance_engineering.qmd\",\n    \"line\": 706,\n    \"message\": \"Closed name decode_ms_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/security_privacy/security_privacy.qmd\",\n    \"line\": 1455,\n    \"message\": \"Closed name alert_interquery_ms_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 271,\n    \"message\": \"Closed name energy_kwh_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 927,\n    \"message\": \"Closed name operational_tonnes_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 929,\n    \"message\": \"Closed name embodied_tonnes_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 930,\n    \"message\": \"Closed name total_tonnes_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 1647,\n    \"message\": \"Closed name grid_ci_g_per_kwh_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 1659,\n    \"message\": \"Closed name embodied_daily_kg_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 1660,\n    \"message\": \"Closed name embodied_training_kg_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 1838,\n    \"message\": \"Closed name embodied_daily_kg_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 3203,\n    \"message\": \"Closed name phone_battery_j_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  },\n  {\n    \"rule\": \"L014\",\n    \"file\": \"books/vol2/sustainable_ai/sustainable_ai.qmd\",\n    \"line\": 3205,\n    \"message\": \"Closed name budget_j_str uses open fmt() \\u2014 use fmt_qty/domain formatter.\",\n    \"severity\": \"warning\"\n  }\n]","isInternal":false,"tokens":5795,"sizeBytes":19113},{"name":"vol1_appendix_algorithm.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_appendix_algorithm.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_appendix_algorithm.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_appendix_algorithm.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_appendix_algorithm.yaml)","tokens":300,"sizeBytes":263},{"name":"vol1_appendix_assumptions.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_appendix_assumptions.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_appendix_assumptions.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_appendix_assumptions.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_appendix_assumptions.yaml)","tokens":300,"sizeBytes":267},{"name":"vol1_appendix_dam.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_appendix_dam.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_appendix_dam.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_appendix_dam.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_appendix_dam.yaml)","tokens":300,"sizeBytes":251},{"name":"vol1_appendix_data.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_appendix_data.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_appendix_data.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_appendix_data.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_appendix_data.yaml)","tokens":300,"sizeBytes":253},{"name":"vol1_appendix_machine.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_appendix_machine.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_appendix_machine.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_appendix_machine.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_appendix_machine.yaml)","tokens":300,"sizeBytes":259},{"name":"vol1_benchmarking.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_benchmarking.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_benchmarking.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_benchmarking.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_benchmarking.yaml)","tokens":300,"sizeBytes":251},{"name":"vol1_conclusion.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_conclusion.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_conclusion.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_conclusion.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_conclusion.yaml)","tokens":300,"sizeBytes":247},{"name":"vol1_data_engineering.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_data_engineering.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_data_engineering.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_data_engineering.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_data_engineering.yaml)","tokens":300,"sizeBytes":259},{"name":"vol1_data_selection.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_data_selection.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_data_selection.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_data_selection.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_data_selection.yaml)","tokens":300,"sizeBytes":255},{"name":"vol1_frameworks.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_frameworks.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_frameworks.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_frameworks.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_frameworks.yaml)","tokens":300,"sizeBytes":247},{"name":"vol1_hw_acceleration.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_hw_acceleration.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_hw_acceleration.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_hw_acceleration.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_hw_acceleration.yaml)","tokens":300,"sizeBytes":257},{"name":"vol1_introduction.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_introduction.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_introduction.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_introduction.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_introduction.yaml)","tokens":300,"sizeBytes":251},{"name":"vol1_ml_lifecycle.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_ml_lifecycle.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_ml_lifecycle.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_ml_lifecycle.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_ml_lifecycle.yaml)","tokens":300,"sizeBytes":251},{"name":"vol1_ml_ops.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_ml_ops.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_ml_ops.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_ml_ops.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_ml_ops.yaml)","tokens":300,"sizeBytes":239},{"name":"vol1_model_compression.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_model_compression.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_model_compression.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_model_compression.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_model_compression.yaml)","tokens":300,"sizeBytes":261},{"name":"vol1_model_serving.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_model_serving.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_model_serving.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_model_serving.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_model_serving.yaml)","tokens":300,"sizeBytes":253},{"name":"vol1_nn_architectures.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_nn_architectures.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_nn_architectures.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_nn_architectures.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_nn_architectures.yaml)","tokens":300,"sizeBytes":259},{"name":"vol1_nn_computation.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_nn_computation.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_nn_computation.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_nn_computation.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_nn_computation.yaml)","tokens":300,"sizeBytes":255},{"name":"vol1_responsible_engr.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_responsible_engr.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_responsible_engr.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_responsible_engr.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_responsible_engr.yaml)","tokens":300,"sizeBytes":259},{"name":"vol1_system_paradigms.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_system_paradigms.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_system_paradigms.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_system_paradigms.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_system_paradigms.yaml)","tokens":300,"sizeBytes":259},{"name":"vol1_training.yaml","path":"binder/tools/audits/mlsysim_constants/vol1_training.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_training.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol1_training.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol1_training.yaml)","tokens":300,"sizeBytes":243},{"name":"vol2_appendix_assumptions.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_appendix_assumptions.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_assumptions.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_appendix_assumptions.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_assumptions.yaml)","tokens":300,"sizeBytes":267},{"name":"vol2_appendix_c3.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_appendix_c3.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_c3.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_appendix_c3.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_c3.yaml)","tokens":300,"sizeBytes":249},{"name":"vol2_appendix_communication.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_appendix_communication.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_communication.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_appendix_communication.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_communication.yaml)","tokens":300,"sizeBytes":271},{"name":"vol2_appendix_dam.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_appendix_dam.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_dam.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_appendix_dam.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_dam.yaml)","tokens":300,"sizeBytes":251},{"name":"vol2_appendix_fleet.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_appendix_fleet.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_fleet.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_appendix_fleet.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_fleet.yaml)","tokens":300,"sizeBytes":255},{"name":"vol2_appendix_reliability.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_appendix_reliability.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_reliability.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_appendix_reliability.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_appendix_reliability.yaml)","tokens":300,"sizeBytes":267},{"name":"vol2_collective_communication.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_collective_communication.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_collective_communication.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_collective_communication.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_collective_communication.yaml)","tokens":300,"sizeBytes":275},{"name":"vol2_compute_infrastructure.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_compute_infrastructure.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_compute_infrastructure.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_compute_infrastructure.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_compute_infrastructure.yaml)","tokens":300,"sizeBytes":271},{"name":"vol2_conclusion.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_conclusion.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_conclusion.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_conclusion.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_conclusion.yaml)","tokens":300,"sizeBytes":247},{"name":"vol2_data_storage.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_data_storage.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_data_storage.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_data_storage.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_data_storage.yaml)","tokens":300,"sizeBytes":251},{"name":"vol2_distributed_training.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_distributed_training.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_distributed_training.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_distributed_training.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_distributed_training.yaml)","tokens":300,"sizeBytes":267},{"name":"vol2_edge_intelligence.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_edge_intelligence.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_edge_intelligence.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_edge_intelligence.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_edge_intelligence.yaml)","tokens":300,"sizeBytes":261},{"name":"vol2_fault_tolerance.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_fault_tolerance.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_fault_tolerance.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_fault_tolerance.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_fault_tolerance.yaml)","tokens":300,"sizeBytes":257},{"name":"vol2_fleet_orchestration.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_fleet_orchestration.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_fleet_orchestration.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_fleet_orchestration.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_fleet_orchestration.yaml)","tokens":300,"sizeBytes":265},{"name":"vol2_inference.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_inference.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_inference.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_inference.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_inference.yaml)","tokens":300,"sizeBytes":245},{"name":"vol2_introduction.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_introduction.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_introduction.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_introduction.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_introduction.yaml)","tokens":300,"sizeBytes":251},{"name":"vol2_network_fabrics.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_network_fabrics.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_network_fabrics.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_network_fabrics.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_network_fabrics.yaml)","tokens":300,"sizeBytes":257},{"name":"vol2_ops_scale.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_ops_scale.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_ops_scale.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_ops_scale.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_ops_scale.yaml)","tokens":300,"sizeBytes":245},{"name":"vol2_performance_engineering.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_performance_engineering.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_performance_engineering.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_performance_engineering.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_performance_engineering.yaml)","tokens":300,"sizeBytes":273},{"name":"vol2_responsible_ai.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_responsible_ai.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_responsible_ai.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_responsible_ai.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_responsible_ai.yaml)","tokens":300,"sizeBytes":255},{"name":"vol2_robust_ai.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_robust_ai.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_robust_ai.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_robust_ai.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_robust_ai.yaml)","tokens":300,"sizeBytes":245},{"name":"vol2_security_privacy.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_security_privacy.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_security_privacy.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_security_privacy.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_security_privacy.yaml)","tokens":300,"sizeBytes":259},{"name":"vol2_sustainable_ai.yaml","path":"binder/tools/audits/mlsysim_constants/vol2_sustainable_ai.yaml","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_sustainable_ai.yaml","title":"Mlsysim_constants Skill","category":"anthropic-skill","format":"yaml","content":"# Mlsysim_constants Skill\n\nPath: `binder/tools/audits/mlsysim_constants/vol2_sustainable_ai.yaml`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/vol2_sustainable_ai.yaml)","tokens":300,"sizeBytes":255},{"name":"bib_lint_baseline.json","path":"binder/tools/bib_lint_baseline.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/bib_lint_baseline.json","title":"Tools Skill","category":"anthropic-skill","format":"json","content":"{\n  \"description\": \"bib_lint allow-list: pre-existing violations grandfathered at the time of the baseline. New violations NOT in this file will block commits. Regenerate via: python3 binder/tools/bib_lint.py --all --baseline\",\n  \"generated\": \"2026-04-08\",\n  \"allowed\": [\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"ahn2022saycan\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"alshiekh2018safe\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"amanatides1987fast\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"ames2014control\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"annpureddy2011staliro\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"assran2023self\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"banerjee2018hands\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@inproceedings missing required field `publisher`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"barfoot2017state\",\n      \"rule\": \"missing-required-field\",\n      \"message\": \"@article missing required field `journal`\"\n    },\n    {\n      \"file\": \"books/vol4/references.bib\",\n      \"key\": \"bishop1998methodology\",\n      \"rule\": 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\"publisher-not-canonical\",\n      \"severity\": \"info\",\n      \"message\": \"publisher `Association for Computing Machinery (ACM)` is not in the canonical set; verify it matches \\u00a75's publisher mapping table\"\n    },\n    {\n      \"file\": \"books/references-vol3.bib\",\n      \"key\": \"denning1968\",\n      \"rule\": \"publisher-not-canonical\",\n      \"severity\": \"info\",\n      \"message\": \"publisher `Association for Computing Machinery (ACM)` is not in the canonical set; verify it matches \\u00a75's publisher mapping table\"\n    },\n    {\n      \"file\": \"books/references-vol3.bib\",\n      \"key\": \"ferguson2012jockey\",\n      \"rule\": \"publisher-not-canonical\",\n      \"severity\": \"info\",\n      \"message\": \"publisher `Association for Computing Machinery` is not in the canonical set; verify it matches \\u00a75's publisher mapping table\"\n    },\n    {\n      \"file\": \"books/references-vol3.bib\",\n      \"key\": \"garciamolina1987sagas\",\n      \"rule\": \"publisher-not-canonical\",\n      \"severity\": \"info\",\n      \"message\": \"publisher `Association for Computing Machinery` is not in the canonical set; verify it matches \\u00a75's publisher mapping table\"\n    },\n    {\n      \"file\": \"books/references-vol3.bib\",\n      \"key\": \"goodhart1984\",\n      \"rule\": \"publisher-not-canonical\",\n      \"severity\": \"info\",\n      \"message\": \"publisher `Palgrave` is not in the canonical set; verify it matches \\u00a75's publisher mapping table\"\n    },\n    {\n      \"file\": \"books/references-vol3.bib\",\n      \"key\": \"grandl2014\",\n      \"rule\": \"publisher-not-canonical\",\n      \"severity\": \"info\",\n      \"message\": \"publisher `Association for Computing Machinery` is not in the canonical set; verify it matches \\u00a75's publisher mapping table\"\n    },\n    {\n      \"file\": \"books/references-vol3.bib\",\n      \"key\": \"gray1986computers\",\n      \"rule\": \"title-suspect-titlecase-function\",\n      \"severity\": \"info\",\n      \"message\": \"title may be in Title Case: \\u00a75 prefers sentence case; verify capitalized The/And/... mid-title (ignore if intentional name)\"\n    },\n    {\n      \"file\": \"books/references-vol3.bib\",\n      \"key\": \"gunasekar2023textbooks\",\n      \"rule\": \"author-initials-only\",\n      \"severity\": \"warning\",\n      \"message\": \"author list uses initials for some first names; \\u00a75 prefers full first names when discoverable\"\n    },\n    {\n      \"file\": \"books/references-vol3.bib\",\n      \"key\": \"guo2016rdma\",\n      \"rule\": \"publisher-not-canonical\",\n      \"severity\": \"info\",\n      \"message\": \"publisher `Association for Computing","isInternal":false,"tokens":13367,"sizeBytes":50000},{"name":"katex_builtins.json","path":"binder/tools/notation/katex_builtins.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/notation/katex_builtins.json","title":"Notation Skill","category":"anthropic-skill","format":"json","content":"# Notation Skill\n\nPath: `binder/tools/notation/katex_builtins.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/notation/katex_builtins.json)","tokens":300,"sizeBytes":204},{"name":"package-lock.json","path":"binder/tools/notation/package-lock.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/notation/package-lock.json","title":"Notation Skill","category":"anthropic-skill","format":"json","content":"# Notation Skill\n\nPath: `binder/tools/notation/package-lock.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/notation/package-lock.json)","tokens":300,"sizeBytes":200},{"name":"package.json","path":"binder/tools/notation/package.json","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/notation/package.json","title":"Notation Skill","category":"anthropic-skill","format":"json","content":"# Notation Skill\n\nPath: `binder/tools/notation/package.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/notation/package.json)","tokens":300,"sizeBytes":190},{"name":"citation_reference_workflow.md","path":"binder/tools/scripts/audit/citation_reference_workflow.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/audit/citation_reference_workflow.md","title":"Audit Skill","category":"anthropic-skill","format":"markdown","content":"# Audit Skill\n\nPath: `binder/tools/scripts/audit/citation_reference_workflow.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/audit/citation_reference_workflow.md)","tokens":300,"sizeBytes":233},{"name":"README_INDEX_PLACEMENT.md","path":"binder/tools/scripts/content/README_INDEX_PLACEMENT.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/content/README_INDEX_PLACEMENT.md","title":"Content Skill","category":"anthropic-skill","format":"markdown","content":"# Content Skill\n\nPath: `binder/tools/scripts/content/README_INDEX_PLACEMENT.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/content/README_INDEX_PLACEMENT.md)","tokens":300,"sizeBytes":229},{"name":"FIGURE_CAPTIONS.md","path":"binder/tools/scripts/docs/FIGURE_CAPTIONS.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/docs/FIGURE_CAPTIONS.md","title":"Docs Skill","category":"anthropic-skill","format":"markdown","content":"# Docs Skill\n\nPath: `binder/tools/scripts/docs/FIGURE_CAPTIONS.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/docs/FIGURE_CAPTIONS.md)","tokens":300,"sizeBytes":206},{"name":"SECTION_ID_SYSTEM.md","path":"binder/tools/scripts/docs/SECTION_ID_SYSTEM.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/docs/SECTION_ID_SYSTEM.md","title":"Docs Skill","category":"anthropic-skill","format":"markdown","content":"# Docs Skill\n\nPath: `binder/tools/scripts/docs/SECTION_ID_SYSTEM.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/docs/SECTION_ID_SYSTEM.md)","tokens":300,"sizeBytes":210},{"name":"WORKFLOW_CLEANUP.md","path":"binder/tools/scripts/docs/WORKFLOW_CLEANUP.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/docs/WORKFLOW_CLEANUP.md","title":"Docs Skill","category":"anthropic-skill","format":"markdown","content":"# Docs Skill\n\nPath: `binder/tools/scripts/docs/WORKFLOW_CLEANUP.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/docs/WORKFLOW_CLEANUP.md)","tokens":300,"sizeBytes":208},{"name":"AU_QUERY_RESPONSES.md","path":"binder/tools/scripts/mit_press/AU_QUERY_RESPONSES.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/mit_press/AU_QUERY_RESPONSES.md","title":"Mit_press Skill","category":"anthropic-skill","format":"markdown","content":"# Mit_press Skill\n\nPath: `binder/tools/scripts/mit_press/AU_QUERY_RESPONSES.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/mit_press/AU_QUERY_RESPONSES.md)","tokens":300,"sizeBytes":227},{"name":"STYLE.md","path":"tinytorch/guide/tools/diagrams/STYLE.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/tinytorch/guide/tools/diagrams/STYLE.md","title":"Diagrams Skill","category":"anthropic-skill","format":"markdown","content":"# Diagrams Skill\n\nPath: `tinytorch/guide/tools/diagrams/STYLE.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/tinytorch/guide/tools/diagrams/STYLE.md)","tokens":300,"sizeBytes":200},{"name":"RELEASE_TESTING.md","path":"tinytorch/tools/RELEASE_TESTING.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/tinytorch/tools/RELEASE_TESTING.md","title":"Tools Skill","category":"anthropic-skill","format":"markdown","content":"# TinyTorch Release Testing\n\nWhat must be true before a release ships, how to check it, and why each check\nexists. Every gate below corresponds to a defect actually found in the\npre-release cleanup of 2026-09 — none are hypothetical.\n\n## Run it\n\n```bash\npython3 tools/release_check.py          # all gates (training tests can take 15+ min)\npython3 tools/release_check.py --fast   # skip the two slow gates (~10 s)\npython3 tools/release_check.py --list   # show gates without running\npython3 tools/release_check.py -k spine # run one gate\n```\n\nExit code is 0 only when every non-advisory gate passes.\n\n`--fast` is the pre-commit loop. The full run is the pre-release gate; it adds\nthe student-journey simulation and the pytest suite, which together take most of\nthe wall time.\n\n---\n\n## The gates\n\n### Structure — every module looks the same\n\nA student who learns the shape of one module should navigate any of the other\nnineteen without relearning it.\n\n| Gate | What it enforces |\n|---|---|\n| 20 modules, numbered 1–20, each with an export target | No gaps, and every module declares `#\\| default_exp` |\n| Imports after Dependencies, before Introduction | Setup cannot execute before its prerequisite explanation (2026-09-11 audit gate) |\n| The 13-section spine, in order | 🔗 Prerequisites → 🎯 Learning Objectives → 📦 Where This Code Lives → 📋 Module Dependencies → 💡 Introduction → 📐 Foundations → 🏗️ Implementation → 🔧 Integration → 📊 Systems Analysis → 🧪 Module Integration Test → 🤔 Reflection Questions → ⭐ Aha Moment → 🚀 MODULE SUMMARY |\n| No duplicate `##` headings | Two identical headings are indistinguishable in the Colab table of contents |\n| Subtitled headings use `: ` | 154 used a colon, 26 used a dash |\n| MODULE SUMMARY subsections, in order | Key Accomplishments → Systems Insights Discovered → Ready for Next Steps → Export with → **Next** |\n\n**The emoji contract.** The emoji is what students internalize, so it must mean\nthe same thing everywhere: 💡 motivation, 📐 theory, 🏗️ things you build, 🔧\nwiring them together, 📊 measurement, 🧪 tests, ⚠️ hazards. Module 15 once marked\nfour sections 🔧 that were each followed by an exercise; module 17 used 🔧 for a\nsection module 14 marks 📊. The spine gate catches missing sections; emoji\nmisuse inside a section is still a human review item.\n\n### nbgrader — the metadata must be honest\n\n| Gate | What it enforces |\n|---|---|\n| Exactly three canonical header shapes | exercise / graded test / given code, nothing else |\n| `solution: true` implies `BEGIN/END SOLUTION` | 56 cells were marked as exercises with nothing to fill in — imports, setup, demos. They survived only because `ClearSolutions.enforce_metadata = False` |\n| `grade_id` unique within a module | Duplicates make nbgrader's mapping ambiguous |\n\nCurrent counts: **155 exercises, 195 graded tests, 73 given cells.** (2026-09-20; these drift every release, so re-measure rather than trusting the number.)\n\n### Pedagogy — the notebook must read\n\n| Gate | What it enforces |\n|---|---|\n| Every exercise has a markdown cell before it | 15 exercises once had none. Module 06 had **seven consecutive** under a heading about a different function |\n| Every unit test has a What/Why/Expected header | 19 of 20 modules did this; module 17 had none |\n| Exercise docstrings carry TODO and APPROACH | The scaffold students follow |\n| Reflection Questions render as markdown | Module 15's was a code cell showing a raw Python string |\n| Unit-test docstrings open with 🧪 | 19 across four modules opened with a bare `Test`, and one still carried the retired 🔬 |\n| An exercise is followed by its test, not by more exercises | A student should not write several components before any is checked. Module 14 asked for nine profiling helpers in a row and tested them 1,100 lines later; module 06 ran to ten. Limit is five, since a family of small classes may legitimately share one test |\n\n### Progressive disclosure — nothing arrives early\n\n| Gate | What it enforces |\n|---|---|\n| No module imports from a later-numbered module | Hard gate. Currently clean |\n| Forward references are framed as previews | **Advisory** — a regex cannot judge a roadmap diagram or a mid-sentence pointer. Read the warnings; do not treat them as failures |\n\n### Package surface — what students import must exist\n\n| Gate | What it enforces |\n|---|---|\n| Every export target imports | All 20 `tinytorch.*` modules load |\n| Every documented import resolves | Each \"Where This Code Lives\" block is executable. This is the gate that caught `OlympicEvent` never being exported because `#\\| export` sat below an import line instead of at the top of its cell |\n| No unreferenced zero-arg demo functions | 16 of 20 modules call their analysis functions under `if __name__ == \"__main__\"` so students see output. Seven were defined and never called. Functions that take arguments are utilities, not demos, and are exempt |\n\n### Tests — a green suite must mean something\n\n| Gate | What it enforces |\n|---|---|\n| No test signals failure with a bare `return` | pytest discards the value. **Thirteen tests could not fail; six were actually failing** |\n| No exception handler asserts success | Missing implementations or incompatible APIs must not become `assert True` (2026-09-11 audit gate) |\n| No bare `except:` | Six swallowed real failures. The worst skipped the gradient update entirely, turning \"the network never trained\" into a pass |\n| No graded cell swallows its own failure | A handler whose body is only a `pass` or a `print` makes the points unreachable. Module 19's ten-point plotting test caught every exception and passed, so the method could draw nothing and still score full marks. The expected-raise idiom is exempt |\n| Every test file imports and collects | Catches a stale import before the suite runs |\n| Source-built reference regressions | Exports all instructor solutions from `src/` into a temporary package and checks graph lifetime, gradients, loss/shape boundaries, optimizer/checkpoint state, profiling, pruning, quantization, distillation, and cached generation; stale local exports cannot hide failures |\n| Notebook inventory | Requires exactly the 20 notebooks corresponding to the sources before attempting the journey |\n\n### Slow gates\n\n| Gate | What it enforces |\n|---|---|\n| Student journey | All 20 instructor notebooks execute end-to-end as `__main__`, each in a fresh interpreter with only earlier modules exported into a temporary package |\n| pytest | The full suite, including the slow training tests, green |\n\nRun `python3 tools/check_reference.py` directly for the numerical regression check.\nIt is also wired into pre-commit and CI. Generate notebooks with\n`python3 -m tito.main dev export --all` before running the journey.\nThis checks the instructor reference progression; student solution stripping\nand completion enforcement are separate concerns.\n\nMilestone accuracy assertions read the named final metric, rather than any\npercentage printed by a script. The CIFAR learning test lives in\n`test_milestones_training.py` and is marked `slow`; construction-only smoke\ntests remain in `test_milestones_smoke.py`.\n\n---\n\n## What the suite itself must not contain\n\nThe gates above police the module sources. The suite under `tests/` is held to\nthe same standard by review, because a test that cannot fail is worse than no\ntest: it occupies the space where a real check would go.\n\nRemoved in the 2026-09 cleanup: a 91-line file with no test functions that\npytest executed as a script on every collection; three files skipped in full\nbecause they tested APIs the framework no longer has; five environment checks\nwhose only reaction to a bad condition was to print a warning; and one CLI check\nwhose own comment said it was informational and would not fail.\n\nFixed at the same time: `--tinytorch`, the educational mode the test README\nrecommends to students, printed `ALL PASSED | 0 passed, 0 total` on a run with\nfailures, because its reporter was never wired to pytest's results.\n\n## Determinism\n\nNineteen `tinytorch` modules carry a module-level `rng = np.random.default_rng(7)`\nthat layer initialization draws from. It is shared and mutable, so how a layer\ninitializes depends on how many draws happened earlier in the session.\n\nTwo tests passed alone and failed inside the suite because of this. Both created\na local `rng = default_rng(7)` believing it seeded `Linear`; it did not, because\n`Linear` reads its own module global. One even carried a comment saying the seed\nwas there to prevent exactly that flake.\n\n`tests/conftest.py` now reseeds all nineteen generators before each test via an\nautouse fixture. **If you add a module with a global RNG, the fixture finds it\nautomatically** — it walks the package rather than using a hardcoded list.\n\nTo confirm order-independence after a change:\n\n```bash\npython3 -m pytest tests/integration/test_training_capabilities.py -q -k xor_learning\npython3 -m pytest tests/integration -q -k xor_learning\npython3 -m pytest tests/ -q --ignore=tests/environment\n```\n\nAll three must agree.\n\n---\n\n## Manual review — what the gates cannot check\n\n1. **Is the explanation any good?** The gates verify a markdown cell exists\n   before each exercise, not that it teaches.\n2. **Is the emoji semantically right?** Enforced for missing sections, not for a\n   section filed under the wrong emoji.\n3. **Grading weights.** Points per exercise currently spans 5.3 (module 06, 21\n   exercises for 111 points) to 50.0 (module 20, two exercises for 100 points).\n   Module totals span 54 (module 15) to 225 (module 19). Deliberate authorial\n   decision, not yet normalized. Re-measure before quoting these; they move\n   every release.\n4. **Book-authored examples and explanatory claims.** Symbol-derived narrative\n   listings are synchronized by `book/tools/listings.py --check`; that\n   does not validate surrounding prose, figures, or separately authored examples.\n\n---\n\n## Adding a gate\n\nWhen a defect is found, add the gate that would have caught it, in\n`tools/release_check.py`:\n\n```python\n@gate(\"category: what must be true\")\ndef g_short_name():\n    errs = []\n    ...                       # append one string per offender\n    return errs               # empty list == pass\n```\n\nUse `slow=True` for anything over a few seconds, and `advisory=True` when the\ncheck is a judgment call that should warn rather than block. The gate's message\nshould name the offender specifically enough to fix without re-deriving it.\n","isInternal":false,"tokens":2424,"sizeBytes":10581},{"name":"README.md","path":"binder/tools/audit/fmt/README.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/fmt/README.md","title":"fmt Documentation","category":"plugin-manifest","format":"markdown","content":"# fmt Documentation\n\nPath: `binder/tools/audit/fmt/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/fmt/README.md)","tokens":300,"sizeBytes":189},{"name":"README.md","path":"binder/tools/audit/math_render/README.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/math_render/README.md","title":"math_render Documentation","category":"plugin-manifest","format":"markdown","content":"# math_render Documentation\n\nPath: `binder/tools/audit/math_render/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/math_render/README.md)","tokens":300,"sizeBytes":213},{"name":"README.md","path":"binder/tools/audit/README.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/README.md","title":"audit Documentation","category":"plugin-manifest","format":"markdown","content":"# binder/tools/audit — Editorial and Registry Audits\n\nDetection tooling that scans textbook content against the house style rules\nand the MLSys·im registry, plus the verification scripts that back the book\nchecks.\n\n**Fmt / notation audit** (inline `{python}` numbers, spurious `.0`): see\n[`fmt/README.md`](fmt/README.md).\n\n### Registry migration build (constants → zoos)\n\nEnd-to-end gate for the completed `mlsysim` registry migration:\n\n```bash\npython3 binder/tools/audit/check_registry_migration_build.py\n```\n\nIndividual tools:\n\n| Script | Purpose |\n|--------|---------|\n| `book_check_registry_sources.py` | Ban legacy flat constants / alias paths in QMD LEGO cells |\n| `generate_appendix_constants.py --verify` | Execute appendix assumption-table cells against live registries |\n| `refresh_mlsysim_constants_yamls.py --finalize` | Mark audit YAML inventory `should_change: false` |\n| `audit_mlsysim_drift.py` | Detect hand-coded canonical constant drift |\n\n---\n\n## Style scan\n\n```\nbinder/tools/audit/\n├── README.md                      — this file\n├── __init__.py\n├── protected_contexts.py          — LineWalker + inline span detection\n├── ledger.py                      — Issue + Ledger JSON model\n├── scan.py                        — scanner CLI\n├── accept_list.py                 — persistent false-positive accept-list\n├── accepted_fps.json              — accepted false positives\n├── verify.py                      — structural verification checks\n├── math_render/                   — rendered HTML/PDF math-leak audits (see math_render/README.md)\n└── checks/\n    ├── __init__.py\n    ├── vs_period.py               — bare 'vs' → 'vs.'\n    ├── compound_prefix.py         — pre-/non- close-up (strict 6-term list)\n    ├── percent_symbol.py          — '%' → 'percent' in body prose\n    ├── lowercase_prose_references.py  — 'Chapter 12' → 'chapter 12'\n    ├── acknowledgements_spelling.py   — British → American\n    ├── binary_units.py            — GiB/TiB in prose (detection only)\n    └── h3_titlecase.py            — H3+ headings in title case (detection only)\n```\n\nThe scanner is read-only. It reports issues; an editor decides each fix in\ncontext.\n\n### Persistent accept-list\n\n`accept_list.py` + `accepted_fps.json` together record editorial verdicts on\nscanner false positives (proper-noun-heavy headings, named principles,\nlegislation, after-colon CMS 8.158 caps, D·A·M/C³ taxonomy axes). After every\nscan, matching issues are flipped from `open` to `accepted` and tagged with the\nsub-rule that justifies them. Match key is `(category, repo-relative file,\nexact `before` line)` — if a heading is intentionally edited, its accept-list\nentry stops matching and the issue correctly returns to `open` for re-review.\n\n```bash\n# Default: accept-list applied, summary shows matched + stale counts\npython3 binder/tools/audit/scan.py --scope vol1 -v\n\n# Report every issue, ignoring the accept-list\npython3 binder/tools/audit/scan.py --scope vol1 --no-accept-list -v\n\n# Use a different accept-list file (e.g. a draft to iterate on)\npython3 binder/tools/audit/scan.py --scope vol1 --accept-list /tmp/draft.json\n```\n\n### Scan usage\n\nAll commands are from the repo root.\n\n```bash\npython3 binder/tools/audit/scan.py --scope vol2 --verbose\npython3 binder/tools/audit/scan.py --scope vol1 --output vol1-ledger.json --verbose\n```\n\nProduces `audit-ledger.json` (or the path given by `--output`).\n\n---\n\n## Check categories\n\n| Category | Rule | Notes |\n|---|---|---|\n| `vs-period` | §10.10 | Bare `vs` in prose |\n| `compound-prefix-closeup` | §10.8 | Strict 6-term list, no extrapolation |\n| `percent-symbol` | §10.2 | HTML attribute filter (width=N%) |\n| `lowercase-prose-references` | §10.4 | Hand-written \"Chapter 12\" |\n| `acknowledgements-spelling` | §10.7 | British → American |\n| `binary-units-in-prose` | §1 | Detection only |\n| `h3-titlecase` | §10.9 | Per-heading judgment required |\n\n---\n\n## Validation anchors\n\nScan times on a cold run from the repo root:\n\n```\n$ python3 binder/tools/audit/scan.py --scope vol1 -v\nTotal: 629 issues across 34 files (0.4s)\n\n$ python3 binder/tools/audit/scan.py --scope vol2 -v\nTotal: 969 issues across 39 files (0.4s)\n```\n\n### Steady-state anchor (2026-04-08)\n\n| Category | vol1 open | vol1 accepted | vol2 open | vol2 accepted |\n|---|---:|---:|---:|---:|\n| vs-period | 0 | 0 | 0 | 0 |\n| compound-prefix-closeup | 0 | 0 | 0 | 0 |\n| percent-symbol | 0 | 0 | 0 | 0 |\n| lowercase-prose-references | 0 | 0 | 0 | 0 |\n| acknowledgements-spelling | 0 | 0 | 0 | 0 |\n| binary-units-in-prose | 0 | 0 | 0 | 0 |\n| h3-titlecase | **61** | 0 | **29** | 0 |\n| concept-term-capitalization | **19** | 0 | **62** | 0 |\n| abbreviation-first-use | **163** | 0 | **111** | 0 |\n| **TOTAL** | **243** | 0 | **202** | 0 |\n\nItem D uses file-level exclusions for `glossary.qmd` (glossaries are\ndefinitions, not first uses) and excludes the `SIFT` homonym (CV meaning vs\nfault-tolerance meaning).\n\nReproduce with `python3 binder/tools/audit/scan.py --scope vol1 -v`.\nRun the detector self-tests with:\n\n```bash\nPYTHONPATH=binder/tools python3 binder/tools/audit/checks/h3_titlecase.py\nPYTHONPATH=binder/tools python3 binder/tools/audit/checks/concept_term_capitalization.py\nPYTHONPATH=binder/tools python3 binder/tools/audit/checks/abbreviation_first_use.py\n```\n\nExpect `41/41 passed`, `32/32 passed`, and `17/17 passed`.\n\n---\n\n## Adversarial test coverage\n\n- `protected_contexts.py`: 14 adversarial tests covering bold definitions,\n  callout titles, table headers, sentence starts, index entries, @-refs,\n  citations, footnote refs, fig-cap attributes, inline code, and inline math.\n- `compound_prefix.py`: 21 tests covering the strict 6-term list,\n  domain-compound preservation, acronym/proper-noun continuation, and\n  case preservation.\n\nRun the adversarial tests inline with each check module during development.\n","isInternal":false,"tokens":1556,"sizeBytes":5988},{"name":"README.md","path":"binder/tools/audits/mlsysim_constants/README.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/README.md","title":"mlsysim_constants Documentation","category":"plugin-manifest","format":"markdown","content":"# mlsysim_constants Documentation\n\nPath: `binder/tools/audits/mlsysim_constants/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audits/mlsysim_constants/README.md)","tokens":300,"sizeBytes":233},{"name":"README.md","path":"binder/tools/dependencies/README.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/dependencies/README.md","title":"dependencies Documentation","category":"plugin-manifest","format":"markdown","content":"# dependencies Documentation\n\nPath: `binder/tools/dependencies/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/dependencies/README.md)","tokens":300,"sizeBytes":204},{"name":"README.md","path":"binder/tools/figures/README.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/figures/README.md","title":"figures Documentation","category":"plugin-manifest","format":"markdown","content":"# figures Documentation\n\nPath: `binder/tools/figures/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/figures/README.md)","tokens":300,"sizeBytes":189},{"name":"README.md","path":"binder/tools/git-hooks/README.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/git-hooks/README.md","title":"git-hooks Documentation","category":"plugin-manifest","format":"markdown","content":"# git-hooks Documentation\n\nPath: `binder/tools/git-hooks/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/git-hooks/README.md)","tokens":300,"sizeBytes":195},{"name":"README.md","path":"binder/tools/README.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/README.md","title":"tools Documentation","category":"plugin-manifest","format":"markdown","content":"# MLSysBook Tools\n\n`binder/tools` contains production tooling for the MLSysBook source tree. These\ntools are part of how the book is built, checked, generated, audited, and\nreleased. Some are called by humans, some by CI, some by Binder commands, and\nsome by Quarto-adjacent generation workflows.\n\nDo not delete, rename, or move anything under this tree only because it looks\nlike a one-off script. First audit actual use in QMD files, Binder commands, CI,\nrelease scripts, documentation, and generated-asset workflows.\n\n## Production Policy\n\n- Treat `binder/tools` as book infrastructure, not scratch space.\n- Before relocating or removing a tool, search for call sites with `rg`, update\n  callers and documentation, and run the relevant validation command.\n- Prefer stable modules or Binder-facing entrypoints for new book dependencies.\n  Scripts may remain as compatibility entrypoints when they are already part of\n  production workflows.\n- Generated assets should record their source tool in the nearby README or\n  comments so future editors can regenerate rather than hand-edit them.\n- Tooling that depends on external packages should document the runtime command\n  and any special environment setup.\n\n## Current Areas\n\n| Area | Purpose |\n|---|---|\n| `scripts/` | Python and shell entrypoints for generation, maintenance, release, and Quarto-adjacent workflows. |\n| `audit/` | Durable audit records and audit helpers used to track book quality work. |\n| `dependencies/` | Dependency and environment documentation. |\n| `git-hooks/` | Repository hook documentation and related setup. |\n\n## Figure Tool Ownership\n\nThe matplotlib figure style (palette, font stack, font sizes, figure size, and\nthe `setup_plot()` helper) has one source: `mlsysim/mlsysim/viz/style.py`,\nalongside the simulator-aware plotters in `mlsysim.viz`. Every figure, whether\na chapter cell or an `mlsysim` plotter, inherits the same sizes from it.\n\n```text\nmlsysim/mlsysim/viz/\n  style.py        # COLORS, set_book_style(), setup_plot(), BODY_FIGSIZE, MIN_FONT_PT\n  fonts/          # bundled TeX Gyre Heros faces registered by set_book_style()\nbinder/tools/figures/\n  style.py        # re-export of mlsysim.viz.style (the import path chapter cells use)\n```\n\nChapter cells may import either `binder.tools.figures.style` or `mlsysim.viz`;\nboth resolve to the same objects. Define nothing style-related in binder.\n\n`./binder/binder check figures --scope print-scale --volN` renders every\nmatplotlib body figure and checks it against the limits in `viz/style.py`\n(print scale, minimum font size, figures created without the style).\n","isInternal":false,"tokens":595,"sizeBytes":2603},{"name":"README.md","path":"binder/tools/scripts/content/README.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/content/README.md","title":"content Documentation","category":"plugin-manifest","format":"markdown","content":"# content Documentation\n\nPath: `binder/tools/scripts/content/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/content/README.md)","tokens":300,"sizeBytes":205},{"name":"README.md","path":"binder/tools/scripts/docs/README.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/docs/README.md","title":"docs Documentation","category":"plugin-manifest","format":"markdown","content":"# docs Documentation\n\nPath: `binder/tools/scripts/docs/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/docs/README.md)","tokens":300,"sizeBytes":196},{"name":"README.md","path":"binder/tools/scripts/images/README.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/images/README.md","title":"images Documentation","category":"plugin-manifest","format":"markdown","content":"# images Documentation\n\nPath: `binder/tools/scripts/images/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/images/README.md)","tokens":300,"sizeBytes":202},{"name":"README.md","path":"binder/tools/scripts/infrastructure/README.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/infrastructure/README.md","title":"infrastructure Documentation","category":"plugin-manifest","format":"markdown","content":"# infrastructure Documentation\n\nPath: `binder/tools/scripts/infrastructure/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/infrastructure/README.md)","tokens":300,"sizeBytes":226},{"name":"README.md","path":"binder/tools/scripts/README.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/README.md","title":"scripts Documentation","category":"plugin-manifest","format":"markdown","content":"# scripts Documentation\n\nPath: `binder/tools/scripts/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/README.md)","tokens":300,"sizeBytes":189},{"name":"README.md","path":"binder/tools/scripts/socratiQ/README.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/socratiQ/README.md","title":"socratiQ Documentation","category":"plugin-manifest","format":"markdown","content":"# socratiQ Documentation\n\nPath: `binder/tools/scripts/socratiQ/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/socratiQ/README.md)","tokens":300,"sizeBytes":208},{"name":"README.md","path":"binder/tools/scripts/utilities/README.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/utilities/README.md","title":"utilities Documentation","category":"plugin-manifest","format":"markdown","content":"# utilities Documentation\n\nPath: `binder/tools/scripts/utilities/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/scripts/utilities/README.md)","tokens":300,"sizeBytes":211},{"name":"README.md","path":"books/_extensions/mlsysbook-ext/margin-video/README.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/books/_extensions/mlsysbook-ext/margin-video/README.md","title":"margin-video Documentation","category":"plugin-manifest","format":"markdown","content":"# margin-video Documentation\n\nPath: `books/_extensions/mlsysbook-ext/margin-video/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/books/_extensions/mlsysbook-ext/margin-video/README.md)","tokens":300,"sizeBytes":242},{"name":"README.md","path":"books/_extensions/README.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/books/_extensions/README.md","title":"_extensions Documentation","category":"plugin-manifest","format":"markdown","content":"# MLSysBook Extensions\n\nThis directory contains Quarto extensions used by the MLSysBook project.\n\n## ⚠️ CRITICAL WARNING - READ BEFORE MAKING CHANGES\n\n**Some extensions in this directory are HEAVILY CUSTOMIZED and should NEVER be reinstalled using `quarto add`.**\n\n### 🔍 Quick Safety Check\n\nBefore installing or updating any extension, **ALWAYS** check for:\n1. `.CUSTOM_LOCK` files in extension directories\n2. Version numbers ending in `-mlsysbook-custom`\n3. Warnings in extension `_extension.yml` files\n\n### 📋 Extension Inventory\n\n<table width=\"100%\">\n  <thead>\n<tr>\n<th width=\"40%\"><b>Extension</b></th>\n<th width=\"35%\">Status</th>\n<th width=\"25%\">Safe to Update?</th>\n</tr>\n</thead>\n<tbody>\n<tr><td><b>`margin-video`</b></td><td>🚫 **100% Custom**</td><td>Never (MLSysBook only)</td></tr>\n<tr><td><b>`mlsysbook-ext/pseudocode`</b></td><td>🚫 **Customized** (casing, ▷ comments, EPUB)</td><td>Never</td></tr>\n<tr><td><b>`ute/custom-numbered-blocks`</b></td><td>🚫 **Heavy Customization**</td><td>Never</td></tr>\n<tr><td><b>`nmfs-opensci/titlepage`</b></td><td>🚫 **Customized**</td><td>Never</td></tr>\n<tr><td><b>`pandoc-ext/diagram`</b></td><td>✅ Standard</td><td>Yes</td></tr>\n<tr><td><b>`quarto-ext/lightbox`</b></td><td>✅ Standard</td><td>Yes</td></tr>\n</tbody>\n</table>\n\n### 🚨 Emergency Recovery\n\nIf you accidentally overwrote a custom extension:\n```bash\n# Check what changed\ngit status\n\n# Restore from git if needed\ngit checkout HEAD -- book/_extensions/EXTENSION_NAME/\n\n# Run protection check\npython tools/scripts/check_custom_extensions.py\n```\n\n### 📚 Full Documentation\n\nFor complete details, see: [`CUSTOM_EXTENSIONS.md`](./CUSTOM_EXTENSIONS.md)\n\n---\n**When in doubt, DON'T reinstall - ask the team first!**\n","isInternal":false,"tokens":519,"sizeBytes":1749},{"name":"README.md","path":"tinytorch/tinytorch/extensions/README.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/tinytorch/tinytorch/extensions/README.md","title":"extensions Documentation","category":"plugin-manifest","format":"markdown","content":"# extensions Documentation\n\nPath: `tinytorch/tinytorch/extensions/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/tinytorch/tinytorch/extensions/README.md)","tokens":300,"sizeBytes":212},{"name":"README.md","path":"tinytorch/tools/dev/README.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/tinytorch/tools/dev/README.md","title":"dev Documentation","category":"plugin-manifest","format":"markdown","content":"# dev Documentation\n\nPath: `tinytorch/tools/dev/README.md`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/tinytorch/tools/dev/README.md)","tokens":300,"sizeBytes":183},{"name":"README.md","path":"tinytorch/tools/README.md","rawUrl":"https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/tinytorch/tools/README.md","title":"tools Documentation","category":"plugin-manifest","format":"markdown","content":"# Development Tools\n\nThis directory contains tools for TinyTorch maintainers and contributors.\n\n## Structure\n\n- **`release_check.py`** - The pre-release gate suite. `--fast` runs the 34 quick\n  gates; the full run adds the top-to-bottom notebook journey and the pytest\n  suite. `--list` prints every gate. See `RELEASE_TESTING.md`.\n- **`check_reference.py`** - Builds the instructor solutions into a temporary\n  package and runs the numerical and training regressions against it, so a stale\n  local export cannot make the check pass.\n- **`validate_nbgrader_config.py`** - Checks the nbgrader cell-header shapes and\n  `grade_id`s across all 20 modules. Expect `Passed: 20, Failed: 0`.\n- **`check_prose_solution_leaks.py`** - Fails if a graded solution is reprinted in\n  prose outside its `BEGIN/END SOLUTION` region.\n- **`check_grading_holes.py`** - Reports graded cells that pass on an empty student\n  notebook, which happens when a cell's assertions only reach regions tagged\n  `role=\"scaffold\"` and therefore shipped pre-solved.\n- **`dev/`** - Development environment setup and utilities.\n\n## For Students\n\nStudents don't need anything in this directory. Use the main setup scripts in the\nproject root.\n\n## For Developers\n\n- `RELEASE_TESTING.md` in this directory describes what each gate covers and what\n  it deliberately does not.\n- `../MODULE_ANATOMY.md` is the specification for how a module is built, and wins\n  whenever a module, a checklist, or an agent prompt disagrees with it.\n- `../CONTRIBUTING.md` covers the branch and release workflow.\n","isInternal":false,"tokens":375,"sizeBytes":1552}],"systemPromptSnippet":"<yakaai_skills repo=\"harvard-edge/cs249r_book\">\n<!-- File: staffml/ARCHITECTURE.md (Tokens: ~3757 | Category: project-spec) -->\n# StaffML Software Architecture\n\n> **High-Level System Architecture & Design Blueprint**\n> **Repository:** `MLSysBook` (`staffml/`)\n> **Platform:** [StaffML (https://mlsysbook.ai/staffml/)](https://mlsysbook.ai/staffml/)\n> **Audience:** Engineers, contributors, and systems researchers inspecting or extending the platform.\n\n---\n\n## 1. System Overview & Philosophy\n\n**StaffML** is an open-source, physics-grounded preparation and evaluation platform for machine learning systems engineers. Unlike conventional software engineering interview prep (which centers on algorithmic complexity and data structures), ML systems interviews require reasoning about physical hardware constraints: memory bandwidth limits, compute rooflines, interconnect bisections, numerical precision, and thermal/power budgets.\n\nThe central design principle of StaffML is:\n> *You can generate the code, but you cannot prompt your way out of a silicon bottleneck.*\n\n```mermaid\ngraph TD\n    subgraph \"1. Source of Truth (Git)\"\n        YAML[\"10,711 Structured YAMLs<br/>staffml/vault/questions/\"]\n        CHAINS[\"843 Socratic Chains<br/>staffml/vault/chains.json\"]\n        TAXONOMY[\"87 Topics & 13 Areas<br/>staffml/vault/taxonomy.yaml\"]\n        REGISTRY[\"Append-Only ID Registry<br/>staffml/vault/id-registry.yaml\"]\n    end\n\n    subgraph \"2. Compiler & Verification Engine\"\n        CLI[\"vault-cli (Python / Typer / Pydantic)\"]\n        CHECK[\"vault check (Fast, Structural & Slow Invariants)\"]\n        BUILD[\"vault build (Parallel Compiler)\"]\n        DB[\"SQLite Database (vault.db)\"]\n        STATIC[\"Static Corpus JSON (corpus.json)\"]\n    end\n\n    subgraph \"3. Serving & Edge Infrastructure\"\n        WORKER[\"Cloudflare Edge Worker (D1 + KV + Vector)\"]\n        LLM_RELAY[\"Multi-Provider LLM Adapter<br/>Groq ➔ OpenAI ➔ Anthropic ➔ Gemini\"]\n    end\n\n    subgraph \"4. Client Application (Next.js 16)\"\n        APP[\"Next.js App Router (16 Routes)\"]\n        PRACTICE[\"Spaced Repetition Practice\"]\n        ROOFLINE[\"Interactive Roofline Engine\"]\n        SIMULATOR[\"3D Parallelism Simulator\"]\n        GAUNTLET[\"Timed Gauntlet Mock Mode\"]\n        CONDUCTOR[\"Live Socratic AI Conductor\"]\n        EXPLORER[\"Radial Sunburst Explorer\"]\n    end\n\n    YAML --> CHECK\n    CHAINS --> CHECK\n    TAXONOMY --> CHECK\n    REGISTRY --> CHECK\n    CHECK --> BUILD\n    BUILD --> DB\n    BUILD --> STATIC\n    DB --> WORKER\n    STATIC --> APP\n    WORKER --> APP\n    APP --> PRACTICE\n    APP --> ROOFLINE\n    APP --> SIMULATOR\n    APP --> GAUNTLET\n    APP --> EXPLORER\n    APP --> CONDUCTOR\n    CONDUCTOR --> LLM_RELAY\n```\n\nThe system is decoupled into four modular pillars:\n1. **The Question Vault**: A human-first, git-tracked corpus of 10,711 validated YAML files conforming to LinkML/Pydantic schemas.\n2. **The Build & Tooling Layer (`vault-cli`)**: A high-performance compiler that validates invariants, tracks content hashes, and compiles SQLite (`vault.db`) and static bundles.\n3. **The Web Application (`app/`)**: A Next.js 16 App Router application supporting dual runtime modes (local static fallback vs edge-connected D1).\n4. **The Edge & LLM Conductor (`vault-worker` & `app/worker`)**: A Cloudflare Edge Worker providing low-latency Socratic mock interviewing via a resilient multi-provider fallback cascade.\n\n---\n\n## 2. Pillar 1: The Question Vault & Data Model\n\n### 2.1 Four-Axis Classification Schema\n\nEvery question in the vault is classified along four orthogonal axes enforced by LinkML schema v1.0 and Pydantic models:\n\n```mermaid\nclassDiagram\n    class Question {\n        +String schema_version\n        +String id\n        +Track track\n        +Level level\n        +Zone zone\n        +String topic\n        +String competency_area\n        +String bloom_level\n        +String title\n        +String scenario\n        +String question\n        +Visual visual\n        +Details details\n        +String status\n        +String provenance\n        +List~ChainRef~ chains\n    }\n\n    class Details {\n        +String realistic_solution\n        +String common_mistake\n        +String napkin_math\n        +List~String~ options\n        +Int correct_index\n        +List~Resource~ resources\n    }\n\n    class Visual {\n        +String kind\n        +String path\n        +String alt\n        +String caption\n    }\n\n    class ChainRef {\n        +String id\n        +Int position\n    }\n\n    Question *-- Details\n    Question o-- Visual\n    Question o-- ChainRef\n```\n\n- **Track (`track`)**: Deployment domain — `cloud`, `edge`, `mobile`, `tinyml`, or `global`.\n- **Level (`level`)**: Bloom's Taxonomy depth — `L1` (Recall), `L2` (Understand), `L3` (Apply), `L4` (Analyze), `L5` (Evaluate), `L6+` (Create/Architect).\n- **Zone (`zone`)**: 11 Ikigai problem zones — `recall`, `fluency`, `implement`, `analyze`, `diagnosis`, `specification`, `evaluation`, `mastery`, `optimization`, `design`, `realization`.\n- **Competency Area (`competency_area`)**: 13 technical disciplines — `architecture`, `compute`, `memory`, `networking`, `optimization`, `deployment`, `latency`, `power`, `precision`, `reliability`, `data`, `parallelism`, `cross-cutting`.\n\n### 2.2 Socratic Chains\n\nQuestions do not exist in isolation; they are linked into **Socratic Chains** (`staffml/vault/chains.json`). A chain represents a pedagogical progression through an ML systems problem:\n1. **Entry Point (L1/L2)**: Establishes baseline facts (e.g. GPU memory bandwidth or FlashAttention tile size).\n2. **Application & Math (L3)**: Requires arithmetic derivation (e.g. arithmetic intensity or KV cache sizing).\n3. **System Breakdown & Analysis (L4/L5)**: Diagnoses bottlenecks under scale (e.g. pipeline bubbles, NCCL ring contention, thermal throttling).\n4. **Architecture & Synthesis (L6+)**: Evaluates holistic trade-offs under competing constraints.\n\nChains support two progression tiers:\n- **Primary Tier**: Strict Bloom monotonic progression ($\\Delta \\in \\{1, 2\\}$).\n- **Secondary Tier**: Lenient coverage sweeps ($\\Delta \\in \\{0, 1, 2, 3\\}$).\n\n### 2.3 Cryptographic Integrity & Merkle Release Hashes\n\nEvery question receives a deterministic `content_hash` (SHA-256 over normalized canonical JSON of semantic fields). Releases compute a **Merkle root** (`release_hash`) over all published question hashes, taxonomy, chains, zones, and release policy. This provides cryptographic verification for academic citation and drift detection across deployments.\n\n---\n\n## 3. Pillar 2: The CLI & Compiler (`vault-cli`)\n\n`vault-cli` is a typed Python package built with Typer and Rich.\n\n```\nvault-cli/\n├── src/vault_cli/\n│   ├── main.py             # CLI entry point\n│   ├── loader.py           # Parallel YAML filesystem loader + sidecar chain joiner\n│   ├── validator.py        # Multi-tier invariant validation\n│   ├── compiler.py         # SQLite / D1 compiler (compiles vault.db)\n│   ├── models.py           # Pydantic schema models\n│   ├── hashing.py          # Deterministic SHA-256 & Merkle tree calculation\n│   ├── legacy_export.py    # Generates public/data/corpus.json\n│   └── commands/           # check, doctor, build, publish, ship, new, promote\n└── tests/                  # Pytest test suite (97 tests)\n```\n\n### 3.1 Invariant Validation Tiers\n\n`vault check` executes three validation tiers:\n- **Fast Tier (<1s)**: Schema validation, unique ID registry check, path lowercase conventions, required fields.\n- **Structural Tier (<10s)**: Cross-references between taxonomy, topics, chains, 3-part `common_mistake` markers (`**The Pitfall:**`, `**The Rationale:**`, `**The Consequence:**`), `napkin_math` structure, and visual asset existence.\n- **Slow Tier**: Link-rot checks across external documentation URLs and LLM math verification.\n\n---\n\n## 4. Pillar 3: Web Application Architecture (`app/`)\n\nThe frontend is built with **Next.js 16 (App Router)**, TypeScript, Tailwind CSS, KaTeX, and Framer Motion.\n\n```mermaid\ngraph LR\n    subgraph \"Data Access Layer (lib/corpus.ts)\"\n        CONFIG{\"vault-config.ts<br/>(static vs worker)\"}\n        LOCAL[\"Fetch /data/corpus.json<br/>(Static Bundle)\"]\n        REMOTE[\"Fetch Cloudflare Worker API<br/>(D1 Queries)\"]\n        CONFIG -->|Static Mode| LOCAL\n        CONFIG -->|Worker Mode| REMOTE\n    end\n\n    subgraph \"Interactive Modules\"\n        SR[\"Spaced Repetition<br/>(lib/progress.ts)\"]\n        ROOF[\"Roofline Engine<br/>(lib/hardware.ts)\"]\n        SIM[\"3D Sim Engine<br/>(lib/simulator.ts)\"]\n        COND[\"AI Conductor<br/>(lib/interview-conductor.ts)\"]\n    end\n\n    LOCAL --> SR\n    REMOTE --> SR\n    SR --> ROOF\n    SR --> SIM\n    SR --> COND\n```\n\n### 4.1 Dual-Mode Runtime Architecture\n\nThe web application supports two runtime modes via `src/lib/vault-config.ts`:\n1. **Worker Mode (`worker`)**: Light initial page load. Fetches catalog metadata initially and retrieves heavy fields (`scenario`, `details.*`) lazily from the Cloudflare Worker API.\n2. **Static Mode (`static`)**: Fully offline-capable and zero-dependency. Bundles the compiled `corpus.json` in `public/data/` for standalone local deployment or static hosting.\n\n### 4.2 Spaced Repetition Engine (`lib/progress.ts`)\n\nStaffML implements an adapted SuperMemo SM-2 spaced repetition algorithm stored locally in browser `localStorage`:\n- **Interval Progression**: Successful recalls advance review intervals (1 day $\\rightarrow$ 3 days $\\rightarrow$ 7 days $\\rightarrow$ 14 days $\\rightarrow$ 30 days).\n- **Mistake Recycling**: Incorrect ratings reset the repetition interval to 1 day, surfacing the question in tomorrow's review queue.\n- **Privacy First**: All candidate progress, ratings, and custom study plans remain 100% browser-local without mandatory user accounts or telemetry tracking.\n\n### 4.3 Interactive Calculators & Simulators\n\n1. **Roofline Model Engine (`app/roofline/page.tsx`, `lib/hardware.ts`)**:\n   - Calculates arithmetic intensity $\\text{AI} = \\frac{\\text{FLOPs}}{\\text{Bytes}}$ against hardware peak compute ($T_{\\text{peak}}$) and memory bandwidth ($B_{\\text{mem}}$).\n   - Computes the hardware ridge point $I_{\\text{ridge}} = \\frac{T_{\\text{peak}}}{B_{\\text{mem}}}$.\n   - Plots operational points for standard workloads (BERT, ResNet, GPT-2, LLaMA-70B FP16/INT8).\n\n2. **Distributed Training Cluster Simulator (`app/simulator/page.tsx`, `lib/simulator.ts`)**:\n   - Models 3D parallelism: Tensor Parallelism (TP), Pipeline Parallelism (PP), Data Parallelism (DP), and ZeRO-1/2/3.\n   - Calculates per-GPU memory breakdown (Weights, Gradients, Optimizer States, Activation Memory).\n   - Computes Ring AllReduce communication latency across hierarchical networks (NVLink intra-node vs InfiniBand NDR inter-node).\n   - Computes Model FLOPs Utilization (MFU), cluster Mean Time Between Failures (MTBF), and end-to-end training durations.\n\n3. **Radial Sunburst Explorer (`app/explore/page.tsx`)**:\n   - Interactive SVG sunburst visualizer enabling drill-down across Track $\\rightarrow$ Competency Area $\\rightarrow$ Topic $\\rightarrow$ Question Level with search filtering.\n\n---\n\n## 5. Pillar 4: Socratic AI Conductor & Multi-Provider Relay\n\nThe live interview experience (`/interview`) pairs candidates with an AI Socratic interviewer powered by `staffml-vault-worker` and `lib/interview-conductor.ts`.\n\n```mermaid\nsequenceDiagram\n    autonumber\n    actor Candidate as Candidate\n    participant UI as Interview UI (app/interview)\n    participant Cond as Conductor Engine (lib/interview-conductor)\n    participant Worker as Cloudflare Edge Worker\n    participant LLM as LLM Provider Cascade\n\n    Candidate->>UI: Selects Track, Level & Duration (e.g. Cloud L4, 30 min)\n    UI->>Cond: Initializes session & selects entry Socratic Chain\n    Cond->>Worker: POST /interview/turn (System Prompt + Question Context + Transcript)\n    Worker->>LLM: Fallback cascade (Groq ➔ OpenAI ➔ Anthropic ➔ Gemini ➔ Workers AI)\n    LLM-->>Worker: Streaming Response + Structured ---CONDUCTOR_META---\n    Worker-->>UI: Relays SSE stream\n    UI->>Candidate: Renders Socratic response\n    Candidate->>UI: Submits napkin math & architectural answer\n    UI->>Cond: Evaluates answer, adjusts depth, or traverses chain\n    Cond->>Worker: Next turn with rubric feedback criteria\n```\n\n### 5.1 Multi-Provider Fallback Cascade\n\nTo ensure 99.99% uptime and low latency for live mock interviews, the Cloudflare Worker relays requests through a prioritized multi-provider cascade:\n1. **Groq** (`llama-3.3-70b-versatile` / `mixtral-8x7b`): Ultra-low time-to-first-token (<200ms).\n2. **OpenAI** (`gpt-4o` / `gpt-4o-mini`): High-accuracy reasoning fallback.\n3. **Anthropic** (`claude-3-5-sonnet` / `claude-3-5-haiku`): Deep architectural critique.\n4. **Google Gemini** (`gemini-2.0-flash` / `gemini-1.5-pro`): Large context window fallback.\n5. **OpenRouter**: Global dynamic routing fallback.\n6. **Cloudflare Workers AI**: Edge-native, zero-external-dependency final fallback.\n\n### 5.2 Conductor Metadata Protocol\n\nAt each Socratic turn, the AI interviewer appends structured metadata:\n```\n---CONDUCTOR_META---\n{\n  \"intent\": \"probe\",\n  \"score\": 75,\n  \"napkin_math_correct\": true,\n  \"concept_tested\": \"PagedAttention KV cache allocation\",\n  \"advance_chain\": false\n}\n```\n`interview-conductor.ts` parses this block to dynamically decide whether to probe deeper, provide hints, retreat to foundational concepts, or advance to the next question in the chain.\n\n---\n\n## 6. Directory Map\n\n| Path | Purpose |\n| :--- | :--- |\n| **`staffml/vault/`** | The question corpus source of truth: 10,711 YAML files, `chains.json`, `taxonomy.yaml`, `id-registry.yaml`. |\n| **`staffml/vault/schema/`** | LinkML v1.0 schema definitions (`question_schema.yaml`, `enums.py`). |\n| **`staffml/vault/visuals/`** | 144 source SVG architectural and memory diagrams. |\n| **`staffml/vault-cli/`** | Python CLI toolchain (`vault` command) for authoring, invariant checking, building, and publishing. |\n| **`staffml/app/`** | Next.js 16 App Router web application (`src/app/`, `src/components/`, `src/lib/`). |\n| **`staffml/app/worker/`** | Next.js serverless worker relay for LLM conductor streaming. |\n| **`staffml/vault-worker/`** | Cloudflare Edge Worker serving D1 database endpoints and search. |\n| **`staffml/paper/`** | Academic publication macros and LaTeX build scripts synchronized with `vault.db`. |\n\n---\n\n## 7. Verification & Build Contract\n\nTo verify the entire software stack locally:\n\n```bash\n# 1. Verify Vault corpus invariants & health\ncd staffml/vault-cli\npython3 -m pytest -o addopts=\"\" tests/\npython3 -m vault_cli.main check\npython3 -m vault_cli.main doctor\n\n# 2. Compile local corpus and database\npython3 -m vault_cli.main build --local\n\n# 3. Test & build Next.js application\ncd ../staffml\nnpm test\nNEXT_PUBLIC_VAULT_FALLBACK=static npm run build\n\n# 4. Test Cloudflare Edge Worker\ncd ../vault-worker\nnpm test\n```\n\n<!-- File: binder/tools/audit/accepted_fps_notation.json (Tokens: ~34 | Category: anthropic-skill) -->\n{\n  \"schema_version\": 1,\n  \"description\": \"Persistent accept-list for notation-consistency scanner false positives / intentional exceptions.\",\n  \"entries\": []\n}\n\n<!-- File: binder/tools/audit/accepted_fps.json (Tokens: ~75 | Category: anthropic-skill) -->\n{\n  \"schema_version\": 1,\n  \"description\": \"Persistent accept-list of editorially reviewed scanner exceptions. The PR 2094 entries preserve Zeljko Godler-approved Volume I pagination: matching is by category, repository-relative file, and exact source line, so any edited line or new violation returns to the open gate.\",\n  \"entries\": []\n}\n\n<!-- File: binder/tools/audit/artifacts/dead_constants_verified.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Artifacts Skill\n\nPath: `binder/tools/audit/artifacts/dead_constants_verified.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/artifacts/dead_constants_verified.json)\n\n<!-- File: binder/tools/audit/artifacts/fmt_design_b_inventory.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Artifacts Skill\n\nPath: `binder/tools/audit/artifacts/fmt_design_b_inventory.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/artifacts/fmt_design_b_inventory.json)\n\n<!-- File: binder/tools/audit/artifacts/registry_migration_manifest.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Artifacts Skill\n\nPath: `binder/tools/audit/artifacts/registry_migration_manifest.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/artifacts/registry_migration_manifest.json)\n\n<!-- File: binder/tools/audit/baselines/captions_baseline.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Baselines Skill\n\nPath: `binder/tools/audit/baselines/captions_baseline.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/baselines/captions_baseline.json)\n\n<!-- File: binder/tools/audit/baselines/scaffold_citation_baseline.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Baselines Skill\n\nPath: `binder/tools/audit/baselines/scaffold_citation_baseline.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/baselines/scaffold_citation_baseline.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/global_backmatter_references.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_backmatter_references.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_backmatter_references.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/global_backmatter_resources_phd_survival_guide.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_backmatter_resources_phd_survival_guide.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_backmatter_resources_phd_survival_guide.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/global_frontmatter_about_about.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_frontmatter_about_about.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_frontmatter_about_about.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/global_frontmatter_acknowledgements_acknowledgements.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_frontmatter_acknowledgements_acknowledgements.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_frontmatter_acknowledgements_acknowledgements.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/global_frontmatter_index.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_frontmatter_index.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_frontmatter_index.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/global_frontmatter_socratiq_socratiq.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/global_frontmatter_socratiq_socratiq.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/global_frontmatter_socratiq_socratiq.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_algorithm.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_algorithm.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_algorithm.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_assumptions.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_assumptions.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_assumptions.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_dam.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_dam.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_dam.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_data.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_data.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_data.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_machine.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_machine.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_appendix_machine.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/vol1_backmatter_glossary_glossary.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_glossary_glossary.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_glossary_glossary.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/vol1_backmatter_references.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_backmatter_references.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_backmatter_references.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/vol1_benchmarking_benchmarking.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_benchmarking_benchmarking.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_benchmarking_benchmarking.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/vol1_conclusion_conclusion.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_conclusion_conclusion.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_conclusion_conclusion.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/vol1_data_engineering_data_engineering.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_data_engineering_data_engineering.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_data_engineering_data_engineering.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/vol1_data_selection_data_selection.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_data_selection_data_selection.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_data_selection_data_selection.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/vol1_frameworks_frameworks.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frameworks_frameworks.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frameworks_frameworks.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/vol1_frontmatter__conventions.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter__conventions.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter__conventions.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/vol1_frontmatter__notation_body.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter__notation_body.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter__notation_body.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/vol1_frontmatter_about.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_about.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_about.json)\n\n<!-- File: binder/tools/audit/data/chapter_terms/vol1_frontmatter_acknowledgements.json (Tokens: ~300 | Category: anthropic-skill) -->\n# Chapter_terms Skill\n\nPath: `binder/tools/audit/data/chapter_terms/vol1_frontmatter_acknowledgements.json`\n\n[View Raw Content on GitHub](https://raw.githubusercontent.com/harvard-edge/cs249r_book/HEAD/binder/tools/audit/data/chapter_terms/vol1_frontmatter_acknowledgements.json)\n\n<!-- ... +143 more modular skills available via /api/skills/harvard-edge/cs249r_book?path={path} -->\n</yakaai_skills>"}