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Found 46 Skills
Owns Python code style for this stack: ruff for lint + format, numpydoc for docstrings. Two responsibilities — (1) place the project's `ruff.toml` from the bundled template once the stack and workspace are in place, and (2) run ruff against any Python files Claude has just generated or edited. Stops at "the touched files pass `ruff check`." TRIGGER when (any of these): (1) a Python file was just created or edited via Write / Edit / MultiEdit — invoke this skill before declaring the task done so ruff is run on the touched files; (2) a fresh ML workspace was just scaffolded by `organize-ml-workspace` and the project has no `ruff.toml` at its root yet — drop the bundled template; (3) the user asks about lint, format, docstring style, or reaches for `black` / `isort` / `flake8` / `pydocstyle` (redirect to ruff — the stack's canonical linter, owned by `data-science-python-stack` Tier 1). SKIP when: the project is non-Python; the only edits in this turn are to Markdown / TOML / JSON / YAML; the file lives in a third-party vendored directory the user doesn't own. HOW TO USE: run ruff manually on the files you just touched — do not configure a PostToolUse hook for this. **Read the "Stop conditions" block and emit the Pre-flight checklist as visible text in your response — both are mandatory before running ruff.**
Python >= 3.11 coding standards. Use when writing Python code. Requires type hints, return types, Google-style docstrings, trailing commas, explicit kwargs, StrEnum with auto(), dataclasses, pytest-style tests.
Use when writing or editing code in an existing codebase — before adding comments, docstrings, try/catch blocks, validation, logging, or TODOs the surrounding file doesn't have, and before explaining your style choices in the reply.
Draft, edit, review, and refine all human-facing writing, from short-form copy to connected prose. Use it whenever readers must follow ideas, context, reasoning, narrative, or tone. Use it across technical surfaces such as package and repository descriptions, README and technical document content or information architecture, CLI wording, JSDoc and docstrings, explanatory source comments, runtime messages, test titles, labels, and repository collaboration through issues, pull requests, and Discussions. Do not use for LICENSE text, formatting-only work, or tasks that neither evaluate nor change wording or information architecture. Agent responses are not a trigger on their own.
Standards and quality gates for code comments, JSDoc/docstrings, technical documentation, and git commit messages. Use to evaluate or write high-signal, concise documentation and eliminate AI comment fluff, over-explanation, ghost commentary, commit message storytelling, and stylistic tells.
Best practices for documenting APIs and code interfaces, eliminating redundant documentation guidance per agent.
Provides templates, standards, and best practices for writing clear, comprehensive technical documentation
Generate or remediate documentation with human-quality writing and style adherence. Use when creating new documentation, rewriting AI-generated content, or applying style profiles. Do not use for slop detection only (use slop-detector) or learning styles (use style-learner).
Enforcement skill for consistent documentation standards
Apply Python style guide conventions to code