rlm
Process files too large to fit in context (>100KB, >2000 lines). Uses Python REPL for structural analysis, LLM queries for semantic reasoning, and subagents for final synthesis. Triggers - large file, big docum...
Discover testing security llm ai skills, compare source repositories and read the instructions for each workflow.
Process files too large to fit in context (>100KB, >2000 lines). Uses Python REPL for structural analysis, LLM queries for semantic reasoning, and subagents for final synthesis. Triggers - large file, big docum...
Master Cohere v2 Chat API with Python, specializing in entity extraction using JSON Schema mode for structured outputs. Use when extracting entities from text, building data extraction pipelines, implementing N...
Master SurrealDB 2.3.x with Python for multi-model database operations including CRUD, graph relationships, vector search, and real-time queries. Use when working with SurrealDB databases, implementing graph tr...
Domain knowledge for extracting eval assertions and generating test invocation prompts from command/agent specs. Used for building promptfoo evaluation configs.
Shape, refine, and stabilize human intent into a canonical prompt artifact. Iteratively clarifies ambiguity until user confirms readiness.
Execute the forged prompt exactly as written. Requires explicit consent and a ready artifact. Deletes artifact after successful execution.
Integrate LLM providers (Claude, GPT, etc.) with emotive-mascot for sentiment-driven emotional responses. Use when connecting to AI services, implementing chat interfaces, or creating emotion-aware conversation...
Generate complete use case implementations for specific industries and scenarios. Use when creating new demo pages, implementing industry-specific mascot integrations, or exploring new application areas.
Build choreographed multi-step emotion sequences (semantic performances) for complex interactions. Use when designing welcome sequences, error recovery flows, or celebration animations.
API integration patterns for autonomous-dev including subprocess safety, GitHub CLI integration, retry logic, authentication, rate limiting, and timeout handling. Use when integrating external APIs or CLI tools...
REST API design best practices, versioning strategies, error handling, pagination, and OpenAPI documentation. Use when designing or implementing REST APIs, HTTP endpoints, or API documentation.
Standardized templates and patterns for integrating skills into agent prompts. Reduces token overhead through reusable skill reference syntax, action verbs, and progressive disclosure usage guidelines.
Standardized output formats for research, planning, implementation, and review agents. Use when generating agent outputs or parsing agent responses.
GAIK (Generative AI Knowledge Management Toolkit) development guidance. Use when working with: structured data extraction from documents/PDFs/audio, schema generation, document parsing (VisionParser, PyMuPDFPar...
Search the Claude Code knowledge base for errors, solutions, decisions, and patterns. Use this to find information from your memory system.
Explicitly save knowledge, patterns, decisions, or learnings to the knowledge base. Use when you want to document something for future reference.
Write specifications at the right depth for any project. Progressive disclosure from quick Linear issues to full AI feature specs. Embeds Linear Method philosophy (brevity, clarity, momentum) with context engin...
Plan the v1→v2→v3 agency progression for AI features. Walk through mapping how autonomy increases over time, define promotion criteria, and generate artifacts for stakeholder alignment. Based on CC/CD framework...
Expert system for designing and architecting AI agent workflows based on proven Meta methodologies. Use when users need to build AI agents, create agent workflows, solve problems using agentic systems, integrat...
[ARCHIVED] Full 4D Context Canvas reference. For new AI features, use /spec --ai. For debugging, use /ai-debug. For quality checks, use /context-check.
Full 5-stage PRD framework for complex features. Use for deep PRD work via /spec --deep full-prd. For quick feature specs, use /spec --feature instead.
Post-launch AI feature calibration workflow. Document error patterns, review eval performance, and decide on agency promotion. Based on CC/CD framework for continuous calibration of AI products.
Expert prompt optimization system for building production-ready AI features. Use when users request help improving prompts, want to create system prompts, need prompt review/critique, ask for prompt optimizatio...
Create, validate, and refine Claude Code skills. Use when: building a new skill, validating an existing skill against best practices, or improving a skill's clarity and execution. Handles skill structure, front...
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.