context-gathering
Focused context retrieval ("context crunching") for large codebases. Automatically activates during code review, refactoring, feature implementation, or debugging in multi-file projects.
Skills correspondant au nom, à la description ou à l’auteur GitHub.
Focused context retrieval ("context crunching") for large codebases. Automatically activates during code review, refactoring, feature implementation, or debugging in multi-file projects.
AI-powered code review using Gemini models
Get a second opinion from Gemini 3 Pro (gemini-3-pro-preview). Accepts text, code, and images as INPUT. Returns TEXT analysis, advice, and feedback. Use for code review, analyzing screenshots, UX feedback, debu...
Build, refine, and evolve OpenCode agents with opinionated, research-backed guidance. Combines documentation research (webfetch, exa, context7, grep.app) with architectural best practices. Use for creating new...
Create and refine OpenCode agents via guided Q&A. Use proactively for agent creation, performance improvement, or configuration design. Examples: - user: "Create an agent for code reviews" → ask about scope, p...
AI-powered code review focusing on bugs, security, and performance
Provides AI consultation workflows, prompt templates, and best practices for multi-model consultation. Use when user asks for "second opinion", "ask codex", "ask gemini", "AI code review", "external AI consulta...
Google Gemini CLI fundamentals for code analysis, review, and validation. Use when (1) executing gemini commands for code review/analysis, (2) configuring models (gemini-3-flash-preview (default)/gemini-3-pro-p...
OpenAI Codex CLI fundamentals for code analysis, review, and validation. Use when (1) executing codex commands for code review/analysis, (2) configuring models (gpt-5.2-codex/gpt-5.2/gpt-5.1-codex-max/codex-min...
Automated PR code review with multi-agent analysis
Use when auditing code for AI authorship, reviewing acquisitions/contractors, verifying academic integrity, or during code review - provides systematic tiered framework for detecting fully AI-generated AND AI-a...
Multi-model AI council for actionable project advice. Leverages Gemini 3 Flash and GPT-5.2 skills in parallel, then synthesizes through an Opus Judge for stage-appropriate, non-overkill recommendations. Use whe...
Consult the Small Council - a multi-LLM deliberation system that gathers independent answers from multiple frontier AI models, has them anonymously rank each other's responses, then synthesizes a consensus answ...
Automated PR code review with multi-agent analysis
AI agent handles code review feedback professionally by categorizing, responding appropriately, and extracting learnings. Use when PR feedback arrives, addressing reviewer comments, or improving from feedback.
AI agent requests effective code reviews through proper preparation, clear descriptions, and appropriate reviewer selection. Use when creating PRs, requesting feedback, or submitting for review.
Interactive code review through conversation. HOUSTON guides review, spawns specialized agents, and helps create Beads for issues found.
Comprehensive multi-agent code review with parallel analysis. Use for thorough code reviews, finding bugs, checking regressions, or getting alternative implementation perspectives.
Ensures proper use of PAL MCP tools (thinkdeep, debug, codereview, consensus, planner) for complex tasks requiring deep analysis, multi-model collaboration, or systematic investigation. Auto-activates when: -...
External AI code review using Codex or Gemini. Reads project.yaml to determine which provider to use for frontend vs backend tasks. Includes hallucination detection to avoid blindly applying AI suggestions.
This skill should be used when the user asks to "execute plan with beads", "implement with persistent tracking", "bead-driven execution", "run plan with subagents", "track tasks across sessions", "use beads for...
Interact with OpenAI Codex CLI for plan review, code review, and complex problem discussion. Supports model selection and multi-round conversations. Usage: /codex-cli [options]
This skill should be used when the user asks to "use the oracle" or "ask the oracle" for deep research, analysis, or architectural questions. The oracle excels at multi-source research combining codebase explor...
Deep Python knowledge for code reviews. Provides detailed guidance on iterables, data structures, standard library, validation, testing, concurrency, APIs, and security.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.