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Runs the comprehensive test suite with pytest, reports coverage statistics, analyzes failures, and attempts automatic fixes. Use when the user wants to run tests, check coverage, or validate that code changes pass the test suite.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | test |
| description | Runs the comprehensive test suite with pytest, reports coverage statistics, analyzes failures, and attempts automatic fixes. Use when the user wants to run tests, check coverage, or validate that code changes pass the test suite. |
| allowed-tools | ["Bash","Read","Edit","Grep","Glob"] |
| user-invocable | true |
Run comprehensive testing and report results:
Output Format: Use clear section headers, timestamps, and structured test result formatting.
Tool Validation: First verify that required tools are installed (uv, pytest) and test configuration exists.
uv run pytest with appropriate timeout handling. If tests timeout, run them in logical sections (e.g., by directory or test file groups) to ensure all tests are executed and results are captured. Always run the complete test suite, even if it requires multiple section runs.Provide a clear summary of:
Prepares and triggers a new Python package release: runs cleanup, validates semantic versioning, updates pyproject.toml and docs, builds with uv, creates a GitHub release, and monitors the publishing workflow. Supports patch/minor/major auto-increment. Use when the user wants to cut a release, bump the version, or publish a new Python package version.
Verify and release a Rust crate or workspace. Bumps version, commits, tags, pushes. CI-driven by default; --local publishes directly.
Interactive lesson-based teaching skill. Researches a topic via the web, builds a structured curriculum of up to 10 lessons, and delivers them one at a time with comprehension questions. Supports difficulty flags (--beginner, --advanced, --expert) and lesson count (--lessons N). Use when the user wants to learn about any topic in a guided, incremental way.
Run a comprehensive multi-agent QA audit of any project. Auto-detects language and framework, then launches parallel agents to audit code quality, architecture, error handling, test coverage, CI/CD, documentation, and security. Use for pre-release validation, periodic quality reviews, or when the user asks for a full project audit.
Runs a quick project health check covering git status, recent commits, GitHub Actions workflow runs, and package build verification. Use when starting a session, before a release, or to get a fast overview of project state.
Runs a complete code quality pipeline: ruff linting and formatting, mypy type checking, and pytest test suite. Use for end-of-session quality checks, pre-release validation, or when the user asks to lint, format, or clean up code.