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Found 66 Skills
Reflect on previus response and output, based on Self-refinement framework for iterative improvement with complexity triage and verification
Reviews code for quality — architecture conformance, anti-patterns, performance issues, maintainability. Read-only analysis that detects circular dependencies, N+1 queries, dead code, naming violations, and layering breaches. Use when the user asks for a code review, wants feedback on code quality, PR review, tech debt analysis, or architecture conformance checks.
Review code for performance: complexity, database/query efficiency, I/O and network cost, memory and allocation behavior, concurrency contention, caching, and latency/throughput regressions. Cognitive-only atomic skill; output is a findings list.
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.
Comprehensive code review workflow - parallel specialized reviews → synthesis
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- Synthesis: 1 Agent summarizes review results Commands: - /把关 - Start pre-publish review - /把关 check - Check unpublished changes - /把关 version - Recommend version upgrade - /把关 report - Generate review report - /review - English command Capabilities: Unpublished change detection,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.
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.
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.