Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Run interactive brainstorming across verifiers environments, evaluations, GEPA, and RL training. Use when the user wants ideation, literature scanning, concept teaching, roadmap planning, or research program design grounded in local CLI sources, verifiers, and RL trainer code.
Classify codebases before modification to choose appropriate development approach
Interactive Python REPL automation with common helpers and best practices
Turn a feature request into a minimal, file-level implementation plan before any code.
Manage persistent memory via OpenMemory MCP. TRIGGER when: user says "remember this", "save to memory", "store this", "recall", "what do you remember about", "check memory", "forget this", "delete memory", "clean up memory", or when agent forms a stable conclusion worth persisting. DO NOT TRIGGER when: user refers to system RAM, process memory, or asks to directly edit memory/MEMORY.md file.
Use when the user asks to "set up types without a build step", "use vanilla JS with types", "configure erasable syntax", or mentions "JSDoc type checking". It provides instructions for modern type safety using JSDoc in browsers and native TypeScript execution in Node.js.
Installs and runs the Code Simplifier subagents for Gemini CLI (Code Reuse Reviewer, Code Quality Reviewer, and Efficiency Reviewer) to review and clean up code changes. Trigger this skill when the user asks to "simplify code", "run code simplifier", "review changes for quality", or "setup review agents".
Expert guide for defining, creating, and invoking custom subagents in Gemini CLI. Trigger this skill when the user wants to create a new specialist agent, define a custom subagent, or learn how to delegate tasks to specialist agents within the Gemini CLI environment.
Architecture and patterns for developing image editor tools and UI in the SwarmUI image editor.
How to effectively use QMD (Quick Markdown Search) to pull in extra relevant context, run multi-query searches, extract high-scoring chunk IDs, and fetch their contents. Use this skill when asked to search across a large markdown knowledge base, run QMD queries, or retrieve deep context using the qmd CLI.