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atsushi-greenatsushi-green/ds-ai-coding-skills/CLAUDE.md

ds-ai-coding-skills

CLAUDE.md86 starsChanged 49 days agoMITView on GitHub

AGENTS.md carries the same content for GitHub Copilot and Codex. Everything from ## Hard Rules onward must match between the two files; scripts/sync_agent_docs.py --check enforces this. The ## Skills section at the end is Claude-specific. This is a Python 3.11 data science / analysis project. Detailed task-specific procedures are in .claude/skills/*/SKILL.md. Project-specific context is in docs/agent/*.

The file

Show its rules and text

We split this CLAUDE.md into the rules it gives an agent

23 rules. About 0 are common, 12 are distinctive, and 11 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈12

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 11

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  • could be automatic: a setting could enforce it
  1. Distinctive:

    Never commit raw data, credentials, API keys, tokens, or customer-level records.

    line 14
  2. Distinctive:

    Never modify, overwrite, delete, or regenerate raw data directly.

    line 15
  3. Distinctive:

    Prefer small, reviewable changes.

    line 16
  4. Distinctive:

    Ask for clarification when data semantics are unclear.

    line 18
  5. Very specific:

    Use uv exclusively for Python dependency management.

    line 19
  6. Very specific:

    When applying a statistical, ML, causal, simulation, or optimization method, always apply the matching *-diagnostics skill (図と値をセットで出す).

    line 20
  7. Distinctive:

    Use uv exclusively for all dependency management.

    line 24
  8. Very specific:

    Never use pip, pip3, python -m pip, poetry, conda, pipenv, or easy_install.

    line 25
  9. Distinctive:

    Never modify or delete raw data directly.

    line 30
  10. Very specific:

    Treat data/raw and data/external as immutable.

    line 31
  11. Very specific:

    Follow python-style skill: type hints, Google-style docstrings, Japanese comments.

    line 59
  12. Very specific:

    Follow dataframe-polars skill: prefer polars over pandas.

    line 60
  13. Very specific:

    Follow path-and-io skill: use pathlib.Path, no absolute paths.

    line 61
  14. Very specific:

    Do not create, modify, or commit real data files under data/raw/ or data/external/ — these are immutable.

    line 65
  15. Very specific:

    Only .gitkeep files and documentation (README, markdown) are acceptable to commit.

    line 67
  16. Very specific:

    Use explicit column names.

    line 72
  17. Distinctive:

    Use CTEs for readability.

    line 73
  18. Distinctive:

    Add date filters for large tables.

    line 74
  19. Very specific:

    Never run DROP, TRUNCATE, DELETE, or UPDATE unless explicitly requested.

    line 76
  20. Distinctive:

    Keep restartable from a clean kernel.

    line 81
  21. Distinctive:

    Write documentation in clear Japanese.

    line 86
  22. Distinctive:

    Keep code snippets, commands, file paths, and config values in English as-is.

    line 87
  23. Distinctive:

    Do not translate technical terms unnecessarily.

    line 88

≈ “Common” is an estimate: at least 1 in 5 of the 26,980 CLAUDE.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
CLAUDE.md

CLAUDE.md

AGENTS.md carries the same content for GitHub Copilot and Codex. Everything from ## Hard Rules onward must match between the two files; scripts/sync_agent_docs.py --check enforces this. The ## Skills section at the end is Claude-specific.

This is a Python 3.11 data science / analysis project.

Detailed task-specific procedures are in .claude/skills/*/SKILL.md. Project-specific context is in docs/agent/*.

Hard Rules (Always Apply)

  • Never commit raw data, credentials, API keys, tokens, or customer-level records.
  • Never modify, overwrite, delete, or regenerate raw data directly.
  • Prefer small, reviewable changes.
  • Explain assumptions before non-trivial analytical decisions.
  • Ask for clarification when data semantics are unclear.
  • Use uv exclusively for Python dependency management. Never use pip, conda, poetry, or pipenv.
  • When applying a statistical, ML, causal, simulation, or optimization method, always apply the matching *-diagnostics skill (図と値をセットで出す).

Package Management

  • Use uv exclusively for all dependency management.
  • Never use pip, pip3, python -m pip, poetry, conda, pipenv, or easy_install.

Data Safety

  • Never commit raw data, credentials, API keys, tokens, or customer-level records.
  • Never modify or delete raw data directly.
  • Treat data/raw and data/external as immutable.

Common Commands

uv sync
uv run pytest
uv run ruff check .
uv run ruff format .          # ローカル整形
uv run ruff format --check .  # CI用(差分チェックのみ)
uv run mypy src
uv run python scripts/check_no_raw_data_commit.py
uv run python scripts/check_no_sensitive_patterns.py

Key Conventions

  • DataFrame operations: prefer polars over pandas.
  • Visualization: use fig, ax = plt.subplots(...), not plt.figure(...).
  • File paths: use pathlib.Path, no absolute local paths.
  • Docstrings: Google-style.
  • Inline comments: Japanese.
  • Reports and documentation: Japanese.

File-Specific Guidelines

Python files (**/*.py)

  • Follow python-style skill: type hints, Google-style docstrings, Japanese comments.
  • Follow dataframe-polars skill: prefer polars over pandas.
  • Follow path-and-io skill: use pathlib.Path, no absolute paths.

Data files (data/**)

  • Do not create, modify, or commit real data files under data/raw/ or data/external/ — these are immutable.
  • Writing derived data to data/interim/ or data/processed/ is allowed in code, but do not commit large data files.
  • Only .gitkeep files and documentation (README, markdown) are acceptable to commit.
  • See safe-data-handling skill.

SQL files (**/*.sql)

  • Use explicit column names; avoid SELECT *.
  • Use CTEs for readability.
  • Add date filters for large tables.
  • Validate join cardinality and row counts.
  • Never run DROP, TRUNCATE, DELETE, or UPDATE unless explicitly requested.
  • See sql-analysis skill.

Notebooks (**/*.ipynb, notebooks/**/*.md)

  • Keep restartable from a clean kernel; no secrets in outputs.
  • See notebook-workflow and safe-data-handling skills.

Documentation (README.md, docs/**/*.md)

  • Write documentation in clear Japanese.
  • Keep code snippets, commands, file paths, and config values in English as-is.
  • Do not translate technical terms unnecessarily.

Skill Routing

TaskSkill
Dependencies, tests, lint, type check, notebook executionpython-project-ops
Reading / writing / moving data filessafe-data-handling + path-and-io
Writing or reviewing SQLsql-analysis
Writing or reviewing Python codepython-style
DataFrame operationsdataframe-polars
Charts and visualizationvisualization
Notebook creation and editingnotebook-workflow
Running any statistical / ML / causal / simulation / optimization methodthe matching *-diagnostics router (5 families, each routing to references/<method>.md): statistical-inference, predictive-modeling, causal-inference, unsupervised-eda, simulation-optimization
Reviewing someone else's statistics or ML workstatistical-ml-review
Analysis summaries and reportsanalysis-reporting
File paths and I/Opath-and-io

Project Context (docs/agent)

このリポジトリでしか通用しない知識だけを置く。作業手順・規約は skill 側が正本であり、 ここには重複させない(持ち運ぶ単位は .claude/skills/<name>/ ディレクトリ)。 ディレクトリ構成は README.md を参照する。

DocumentPurpose
project-overview.mdプロジェクトの目的とスコープ
data-catalog.mdデータセット一覧と定義
metrics-and-definitions.md指標定義
diagnostics-reference-template.md診断 skill(*-diagnostics)への手法追加手順と雛形

Skills

@.claude/skills/python-project-ops/SKILL.md @.claude/skills/python-style/SKILL.md @.claude/skills/dataframe-polars/SKILL.md @.claude/skills/path-and-io/SKILL.md @.claude/skills/safe-data-handling/SKILL.md @.claude/skills/sql-analysis/SKILL.md @.claude/skills/notebook-workflow/SKILL.md @.claude/skills/statistical-ml-review/SKILL.md @.claude/skills/visualization/SKILL.md @.claude/skills/analysis-reporting/SKILL.md

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