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Found 63 Skills
Use when the user wants to review a pull request, understand what a PR changes, assess risk of merging, or check for missing test coverage. Examples: "Review this PR", "What does PR #42 change?", "Is this PR safe to merge?"
Detect common code smells and anti-patterns providing feedback on quality issues a senior developer would catch during review. Use when user opens/views code files, asks for code review or quality assessment, mentions code quality/refactoring/improvements, when files contain code smell patterns, or during code review discussions.
Generate an LLM-optimized project profile for any git repository. Outputs docs/{project-name}.md covering architecture, core abstractions, usage guide, design decisions, and recommendations. Trigger: "/project-profiler", "profile this project", "為專案建側寫"
Validate specifications, implementations, constitution compliance, or understanding. Includes spec quality checks, drift detection, and constitution enforcement.
Comprehensively reviews Python libraries for quality across project structure, packaging, code quality, testing, security, documentation, API design, and CI/CD. Provides actionable feedback and improvement recommendations. Use when evaluating library health, preparing for major releases, or auditing dependencies.
Checkpoint - Pre-publish review with multi-layer deep analysis. Triggers: Preparing to publish an npm package, requiring pre-release review, or checking code change quality. Review Layers: - Per-Change: In-depth analysis of each change group (up to 10 Agents) - Holistic: Parallel review by 5 roles (Architecture/Development/Testing/Security/Documentation) - Synthesis: 1 Agent summarizes review results Commands: - /把关 - Start pre-publish review - /把关 check - Check unpublished changes - /把关 version - Recommend version upgrade - /把关 report - Generate review report - /review - English command Capabilities: Unpublished change detection, in-depth per-change analysis, multi-role review, version recommendation, release risk assessment.
Analyzes codebases to identify refactoring opportunities based on Martin Fowler's catalog of code smells and refactoring techniques. Detects duplicated code, high coupling, complex conditionals, primitive obsession, long functions, and other structural issues. Produces a structured refactoring report with prioritized findings saved to docs/_refacs/. Use when auditing code quality, preparing for a refactoring sprint, or reviewing architectural health. Don't use for style/formatting issues, performance optimization, or security audits.
Technical solution evaluation and code review in the style of Linus Torvalds. Only use this when the user explicitly requests a Linus-style review or explicitly asks for a rigorous evaluation of code changes/technical solutions (e.g., "review changes/code", "evaluate if the solution is appropriate", "check submission standards", "linus-tech-review").
Comprehensive code review workflow - parallel specialized reviews → synthesis
This skill should be used when the user asks to "validate a plugin", "optimize plugin", "check plugin quality", "review plugin structure", or mentions plugin optimization and validation tasks.
This skill should be used when analyzing technical debt in a codebase, documenting code quality issues, creating technical debt registers, or assessing code maintainability. Use this for identifying code smells, architectural issues, dependency problems, missing documentation, security vulnerabilities, and creating comprehensive technical debt documentation.
Reflect on previus response and output, based on Self-refinement framework for iterative improvement with complexity triage and verification