Use this when managing Python dependencies with uv, running tests with pytest, linting with ruff, formatting code, type checking with mypy, or executing notebooks.
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See how to installReview the instructions the agent will receive before you install.
Use this skill when changing dependencies, running tests, linting, formatting, type checking, or executing notebooks.
uv for all dependency installation, synchronization, addition, removal, and updates.python -m pip, poetry, conda, pipenv, or easy_install.requirements.txt.uv add <package> when adding dependencies.uv add --group dev <package> for dev-only dependencies.pyproject.toml and uv.lock after dependency changes.uv sync # Install/synchronize dependencies
uv run pytest # Run tests
uv run ruff check . # Lint
uv run ruff format . # Format
uv run mypy src # Type check
uv run papermill notebooks/input.ipynb notebooks/output.ipynb # Execute notebook
bash scripts/run_quality_checks.sh # Run all quality checks
pyproject.toml, run uv sync.uv run ruff check . and uv run ruff format ..uv run pytest and uv run mypy src.papermill.tests/; keep them fast by minimizing external dependencies.ruff settings live in the [tool.ruff] section of pyproject.toml.mypy settings live in the [tool.mypy] section of pyproject.toml.These run in GitHub Actions CI, and can be run locally before committing.
uv run python scripts/check_no_raw_data_commit.py # rawデータのコミットを検知
uv run python scripts/check_no_sensitive_patterns.py # 秘密情報のパターンを検知
uv run python scripts/validate_agent_docs.py # エージェント文書の必須ファイル確認
uv run python scripts/sync_agent_docs.py --check # CLAUDE.md / AGENTS.md のドリフト検出
bash scripts/run_quality_checks.sh # 上記を含む一括実行
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Use this when summarizing analysis results, writing reports, documenting experiment outcomes, or presenting model evaluation — including structuring findings in Japanese with conclusions, facts, assumptions, interpretations, and caveats.
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因果推論・効果検証（A/B テスト / ABテスト / オンライン実験 / リフト / SRM / CUPED、観察データの処置効果 / ATE / ATT / CATE / 傾向スコア / propensity score / IPW / 二重頑健 / DML / causal forest、準実験 / 差の差 / DiD / イベントスタディ / 操作変数 / IV / 2SLS / 回帰不連続 / RDD / 合成コントロール）を実行したら必ずセットで出す図と値のルーター。 proportions_ztest, chisquare, statsmodels.stats.power, dowhy, econml, causalml, doubleml, propensity, LinearDML, IV2SLS, rdrobust, rddensity, pysyncon, treat*post がコードに現れたとき、またはユーザーが「ABテストの結果を 見て」「施策の効果を推定して」「差の差で」「傾向スコアで揃えて」「閾値前後で比較して」と言ったときに使う。SRM・ バランス・並行トレンド・first-stage に言及がなくても適用する。SKILL.md のルーティング表で設計を特定し、対応する references/<設計>.md を読んでから実行する。実験でない群間比較の検定は statistical-inference-diagnostics、 予測モデルの解釈（SHAP 等）は predictive-modeling-diagnostics を使う。
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Use this when performing DataFrame operations — including loading, filtering, joining, aggregating, transforming, or reshaping tabular data with polars or pandas.
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Use this when creating, editing, executing, or reviewing Jupyter notebooks — including cell structure, kernel management, extracting reusable logic to src/, and ensuring notebooks are restartable.
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Use this when reading from or writing to local files — including constructing file paths with pathlib, creating directories, choosing output locations, and using path utilities from src/analysis_project/paths.py.
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分析を始める前に構造化された分析計画を作成する
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