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Found 111 Skills
Review code for best practices, security issues, and potential bugs. Use when reviewing code changes, checking PRs, analyzing code quality, or performing security audits.
MUST READ before running any ADK evaluation. ADK evaluation methodology — eval metrics, evalset schema, LLM-as-judge, tool trajectory scoring, and common failure causes. Use when evaluating agent quality, running adk eval, or debugging eval results. Do NOT use for API code patterns (use adk-cheatsheet), deployment (use adk-deploy-guide), or project scaffolding (use adk-scaffold).
Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch.
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.
Use when creating or improving golden datasets for AI evaluation. Defines quality criteria, curation workflows, and multi-agent analysis patterns for test data.
Analyze datasets to discover patterns, anomalies, and relationships. Use when exploring data files, generating statistical summaries, checking data quality, or creating visualizations. Supports CSV, Excel, JSON, Parquet, and more.
Analyze sleep data, identify sleep patterns, evaluate sleep quality, and provide personalized sleep improvement recommendations. Supports correlation analysis with other health data.
Evaluates agent skills against Anthropic's best practices. Use when asked to review, evaluate, assess, or audit a skill for quality. Analyzes SKILL.md structure, naming conventions, description quality, content organization, and identifies anti-patterns. Produces actionable improvement recommendations.
Get git records for specified users and days, perform code review for each commit, and generate detailed code review reports
Code review of current git changes, compare to related plan if exists, identify bad engineering, over-engineering, or suboptimal solutions. Use when user asks to review changes, check git diff, validate implementation quality, or assess code changes.
Expert at analyzing documentation quality, coverage, and completeness. Auto-invokes when evaluating documentation health, checking documentation coverage, auditing existing docs, assessing documentation quality metrics, or analyzing how well code is documented. Provides frameworks for measuring documentation effectiveness.
Is this token held by quality wallets or retail noise? SM holder ratio, flow breakdown by label, and recent buyer quality.