Run parallel code reviews with multiple AI agents, then synthesize into one report. Triggers on "review code" or "multi-agent review".
Comprehensive GitHub code review with AI-powered swarm coordination
Comprehensive GitHub code review with AI-powered swarm coordination
Comprehensive code review checklist for pull requests
Master data manipulation, analysis, and visualization with Pandas, NumPy, and Matplotlib
Ask Google Gemini questions about code to understand implementations, architecture, patterns, and debugging. Use when the user asks how code works, where something is implemented, what patterns...
Comprehensive GitHub code review with AI-powered swarm coordination
This skill should be used when the user asks to "research code", "how does X work", "where is Y defined", "who calls Z", "trace code flow", "find usages", "review a PR", "explore this library",...
O(log n) sublinear coverage gap detection with risk-weighted analysis and intelligent test prioritization.
Pragmatic coding standards - concise, direct, no over-engineering, no unnecessary comments
Pragmatic coding standards - concise, direct, no over-engineering, no unnecessary comments
Pragmatic coding standards - concise, direct, no over-engineering, no unnecessary comments
Pragmatic coding standards - concise, direct, no over-engineering, no unnecessary comments
Pragmatic coding standards - concise, direct, no over-engineering, no unnecessary comments
Pragmatic coding standards - concise, direct, no over-engineering, no unnecessary comments
Automated code review against project conventions (CLAUDE.md) and best practices
Ask OpenAI Codex questions about code to understand implementations, architecture, patterns, and debugging. Use when the user asks how code works, where something is implemented, what patterns are...
Intelligent code review dispatcher - automatically selects best reviewer based on context and preferences
This skill teaches how to effectively analyze codebases using the codebase-analyzer MCP tools. Use when exploring new repositories, understanding architecture, detecting patterns, or tracing data flow.
Expert guidance for data analysis, visualization, and Jupyter Notebook development with pandas, matplotlib, seaborn, and numpy.