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Validates and corrects Python shebangs and PEP 723 inline script metadata by applying four shebang-selection rules. Use when auditing or fixing shebangs in Python files — choosing between plain python3 and the uv shebang for standalone scripts with external dependencies, adding or removing PEP 723 metadata blocks to match actual import requirements, checking execute bit presence, or avoiding redundant transitive dependencies when typer is declared.

日本語の概要は準備中です。原文の説明を表示しています。

Use when debugging software, investigating incidents, diagnosing flaky tests, or analyzing performance regressions — enforces structured observation recording with evidence IDs, causality validation, and verification gates to prevent correlation-causation pollution. Use when an agent might otherwise summarize or speculate instead of reporting observed evidence.

日本語の概要は準備中です。原文の説明を表示しています。

Use when working with ruff — this skill's ruff policy and required overrides to Astral's official guidance. Pair with `astral:ruff` (if installed) for general usage.

日本語の概要は準備中です。原文の説明を表示しています。

Use when building dependency-free Python 3.11+ scripts for airgapped, stdlib-only, or restricted environments where third-party package installation is prohibited — triggers on "stdlib-only", "airgapped", "no dependencies", "no internet", "restricted environment", or confirmed environments where external packages cannot be installed.

日本語の概要は準備中です。原文の説明を表示しています。

Investigate pytest failures without treating tests or implementation as automatic authority. Use when diagnosing regressions, debugging test errors, or deciding whether to fix a test or code; trace the contract, product, fixture, and observation before choosing an evidence-backed correction.

日本語の概要は準備中です。原文の説明を表示しています。

Configures CI/CD pipelines for automated Python package publishing to PyPI or GitLab Package Registry. Use when creating GitHub Actions or GitLab CI release workflows, setting up trusted publishing or API token-based PyPI authentication, configuring version management with git tags and hatch-vcs, writing pyproject.toml publishing metadata, testing packages against TestPyPI, or documenting the release process for a Python project.

日本語の概要は準備中です。原文の説明を表示しています。

Use when writing asyncio Python code — async/await coroutines, concurrent I/O with asyncio.gather, task creation and cancellation, semaphore rate limiting, producer-consumer queues, async context managers, async generators, WebSocket servers, aiohttp web scraping, async database operations, run_in_executor for blocking calls, or testing async code with pytest-asyncio. Covers FastAPI and aiohttp patterns, synchronization primitives, timeout handling, and common pitfalls like event loop blocking and missing await.

日本語の概要は準備中です。原文の説明を表示しています。

Reviews Python code across type safety, error handling, security, performance, modern patterns, design clarity, typed-boundary compliance, test quality, and documentation. Use when performing code review, PR review, pre-merge quality checks, or assessing Python for security vulnerabilities, bare except clauses, Any usage outside boundaries, or missing input validation at system boundaries.

日本語の概要は準備中です。原文の説明を表示しています。

Use when building terminal UI apps with the Textual framework — creating widgets, screens, layouts, handling events, managing reactive attributes, testing with Pilot, snapshot testing with pytest-textual-snapshot, or running background workers. Covers App lifecycle, CSS styling, screen stack, custom messages, actions, bindings, and the Worker API.

日本語の概要は準備中です。原文の説明を表示しています。

Auto-selects and enforces the strongest valid Python typing lane for the detected Python version and dependencies — no user input required. Use when adding or tightening type annotations, eliminating Any usage in internal code, designing boundary validators or parsers, choosing between stdlib typing (TypedDict, Protocol, dataclasses), Pydantic models, or Hypothesis property tests, addressing ty or mypy failures, or applying version-specific features (TypeIs, ReadOnly, PEP 695 generics, PEP 649 deferred evaluation). Enforces boundary isolation — raw payloads validated immediately at ingress and returned as typed internal objects.

日本語の概要は準備中です。原文の説明を表示しています。

Python web and API development enforcing strict route/domain/data layer separation, Pydantic v2 strict request-response models, edge-resolved auth, and async-safe HTTP clients. Use when working with FastAPI, Starlette, Django, Flask, HTTP endpoints, request models, authentication flows, async handlers, or any Python web framework task.

日本語の概要は準備中です。原文の説明を表示しています。

Design and run controlled experiments using the experiment-registry MCP server — domain-agnostic, pluggable, mechanically enforced. Use when you need evidence that a change actually improves behaviour.

日本語の概要は準備中です。原文の説明を表示しています。

Specialist skill for Python data engineering — pandas, polars, DuckDB, numpy, ETL pipelines, tabular data ingestion, and notebook-to-module extraction. Use when working with dataframes, data validation at ingress boundaries, merge/join operations, typed column contracts, or choosing between pandas vs polars vs DuckDB for a data task.

日本語の概要は準備中です。原文の説明を表示しています。

Use when diagnosing a Python traceback, failing test, intermittent failure, integration defect, or other unexpected runtime behavior.

日本語の概要は準備中です。原文の説明を表示しています。

Routes Python engineering tasks to specialist skills by matching trigger patterns before any architecture, plan, or code is written. Use when working with Typer CLI frameworks, Rich or Textual terminal UIs, CLI UI/UX design, questionary prompts, FastMCP/MCP servers, ty type checker, uv package manager, Hatchling build backend, TOML editing, pre-commit/prek hooks, async Python, PyPI packaging, complex linting, technical debt modernization, testing workflows, feature development, or stdlib-only scripting.

日本語の概要は準備中です。原文の説明を表示しています。

Use before any CLI/TUI display code is written, modified, or audited — runs the 7-stage discipline (Context, Register, Shape brief, Implement, Critique, Audit, Polish) for Typer, Rich, Textual, and Questionary work, grounded in per-project PRODUCT.md and DESIGN.TUI.md/DESIGN.md. Triggers on output formatting, display design, interactive prompts, visual consistency, TUI layout, progress display, dashboard design, design audit, design polish, design critique, shape brief, register decision (brand-cli vs product-cli), and AI-slop checks.

日本語の概要は準備中です。原文の説明を表示しています。

Review pytest test effectiveness against authoritative contracts, relevant faults, behavior-preserving refactors, realistic boundaries, isolation, and diagnostics. Use for test-quality audits, coverage-gap reviews, regression-test changes, or mocking reviews; preserve existing project gates rather than inventing coverage targets.

日本語の概要は準備中です。原文の説明を表示しています。

Use when working with ty — this skill's ty policy and required overrides to Astral's official guidance. Pair with `astral:ty` (if installed) for general usage.

日本語の概要は準備中です。原文の説明を表示しています。

Use when facing unknowns, debugging without a clear cause, or making architecture decisions — enforces hypothesis-driven scientific reasoning through observation, hypothesis formulation, prediction, experiment design, and evidence-based conclusion. Use when previous attempts have failed or the problem space involves uncertainty.

日本語の概要は準備中です。原文の説明を表示しています。

Use when working with Python tooling — uv package management, Hatchling build backend, ty or mypy type checker configuration, ruff linting, pre-commit hook setup, TOML read-write with tomlkit or tomllib, or PyPI packaging and release workflows. Routes to standalone specialist skills for deep dives on any single tool.

日本語の概要は準備中です。原文の説明を表示しています。

Use when implementing a Python feature, adding CLI commands, writing pytest suites, reviewing Python code, debugging, or refactoring. The primary Python engineering workflow orchestrator — classifies the task and delegates through this plugin's own specialist agents (architect → implement → test → review), sized to the task. Delegates to python-cli-architect (implementation), python-pytest-architect (tests), code-reviewer (review), python-cli-design-spec (architecture). Triggers on any Python task requiring specialist agent coordination or multi-agent execution.

日本語の概要は準備中です。原文の説明を表示しています。

Shared Python 3.11+ development rules — type safety and the boundary policy for `Any` (ty, native generics, Protocol, TypeIs, Pydantic), layered architecture and SOLID, error handling, security, performance, identifier naming, PEP 723 script dependencies, Rich/Typer output, tooling defaults (uv, ruff, ty, hatchling, pytest), and testing requirements (behavioral coverage, TDD). Activates when any Python skill or agent needs the shared rules for implementation, code review, refactoring, or test authoring.

日本語の概要は準備中です。原文の説明を表示しています。

Analyze, improve, or represent processes across a file or directory by delegating to process-siren. Uses the same semantic model and validation loop as single-process work; Mermaid is produced when it is the useful concise representation.

日本語の概要は準備中です。原文の説明を表示しています。

Use when building CLI applications with Typer and Rich — creating commands with Annotated parameter syntax, defining arguments and options, composing subcommands, async concurrent CLI tasks with semaphores, testing with CliRunner, PEP 723 shebang scripts, progress bars, Rich terminal output, or non-TTY display width handling.

日本語の概要は準備中です。原文の説明を表示しています。