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Found 71 Skills
Open source contribution best practices. Creating quality pull requests, writing good issues, following project conventions, and collaborating effectively with maintainers.
Periodic repository health check — dependencies, git, CI/CD, code quality, docs, security. Use when: onboarding to a repo, weekly maintenance, after big refactors, before audits, "is this repo in good shape?". Triggers: "repo hygiene", "health check", "repo health", "clean up repo", "maintenance check", "audit repo", "repo audit".
Unified code review system — dispatches the right review agents for the situation. Use when reviewing code for quality, bugs, compliance, or before merging.
Three-lens code review using parallel subagents: Epimetheus (hindsight — bugs, debt, fragility), Metis (craft — clarity, idiom, fit-for-purpose), Prometheus (foresight — vision, extensibility, future-Claude). Triggers on /titans, /review, 'review this code', 'what did I miss', 'before I ship this'. Use after completing substantial work, before /close. (user)
Respond to PR review comments with critical evaluation. Use when addressing code review feedback, responding to bot review comments (Gemini Code Assist, CodeRabbit, etc.), or handling PR suggestions. Fetches comments, evaluates each against project context, applies valid fixes, declines invalid suggestions with reasoning, and posts responses.
Comprehensive GitHub code review with AI-powered swarm coordination
Run Python quality checks with ruff, pytest, mypy, and bandit in deterministic order. Use WHEN user requests "quality gate", "lint", "verify code quality", "check python", or "pre-commit check". Use for pre-merge validation, CI/CD gating, or comprehensive code quality reports. Do NOT use for single-tool runs (run tool directly), debugging runtime bugs (use systematic-debugging), refactoring (use systematic-refactoring), or architecture review.
Comprehensive checklist for conducting thorough code reviews covering functionality, security, performance, and maintainability
Multi-dimensional code review with structured reports. Analyzes correctness, readability, performance, security, testing, and architecture. Triggers on "review code", "code review", "审查代码", "代码审查".
Automated code review with security, performance, and best practices analysis. Use when reviewing pull requests or analyzing code for vulnerabilities, performance issues, or maintainability concerns.
Architecture analysis, violation detection, and pattern validation. USE WHEN: reviewing code architecture, identifying violations, verifying patterns, updating technical documentation. Reference: docs/02-architecture/ARCHITECTURE.md Examples: <example> Context: User wants to check if code follows architecture. user: "Analyze if the payment module follows our architecture" assistant: "I'll use architecture-analyzer to review against ARCHITECTURE.md." <commentary>Architectural review is architecture-analyzer specialty.</commentary> </example> <example> Context: Need to identify technical debt. user: "Find architectural violations in the services layer" assistant: "I'll use architecture-analyzer to scan for violations." <commentary>Violation detection is architecture-analyzer responsibility.</commentary> </example>
Perform systematic self-review of code changes before commits using structured checklist. Validates architecture boundaries, code quality, test coverage, documentation, and project-specific anti-patterns. Use before committing, creating PRs, or when user says "review my changes", "self-review", "check my code". Adapts to Python, JavaScript, TypeScript, Go, Rust projects.