response-quality-analysis
Analyze whether your response addresses the actual question asked before posting. Use when: (1) About to post response to forum/Slack question, (2) Want to validate response coverage, (3) Need to ensure solving the right problem, (4) Want specific improvement suggestions for gaps in response
ai-workflow-engineering
Guide for creating reliable AI workflows and SOPs. Use when: (1) User wants to create a structured workflow for AI tasks, (2) User needs to build an SOP for complex processes, (3) User wants to ensure their workflow follows best practices for managing LLM uncertainty, (4) User mentions creating workflows for domains like code review, response analysis, documentation, or any structured process
guided-ooda-loop
Universal pattern for structured LLM interaction managing finite context windows through phased progression (Observe-Orient-Decide-Act). Use when the user has a complex problem, wants to design/build/create something (software, strategy, document, process), or uses phrases like "I have an idea for...", "help me design...", "guide me through...", or mentions OODA, RPI, or PDD. Reduces hallucinations through structured interaction.
codebase-summary
Analyze a codebase and generate comprehensive documentation including architecture, components, interfaces, workflows, and dependencies. Creates an AI-optimized knowledge base (index.md) and can consolidate into AGENTS.md, README.md, or CONTRIBUTING.md. Use when the user wants to document a codebase, create AGENTS.md, understand system architecture, generate developer documentation, or asks to "summarize the codebase".
prompt-driven-development
Transform rough ideas into detailed design documents with implementation plans. Use when a user wants to develop an idea into a complete specification, create a design document from a concept, plan a feature implementation, or mentions "PDD", "prompt-driven development", "idea to design", "design doc from idea", or wants to systematically refine requirements before building. Guides through requirements clarification, research, detailed design, and implementation planning.
skill-resiliency
This skill should be used when the user asks to "add resiliency to a skill", "make this skill more robust", "improve error handling", "add validation mechanisms", "create self-correcting behavior", or discusses determinism, robustness, error correction, or homeostatic patterns in Agent Skills. Applies biological resiliency principles from Michael Levin's work to Agent Skill design.
transcribing-youtube
Download and transcribe YouTube videos into clean, deduplicated Markdown documents with chapter headings. Wraps yt-dlp to fetch subtitles (manual or auto-generated), removes the rolling-text triplication artifacts from auto-subs, inserts chapter markers from video metadata, and produces both a timestamped transcript and a prose-only version. Use when the user wants to: (1) transcribe a YouTube video, (2) get a transcript or subtitles from YouTube, (3) create an InfoNugget from a video, (4) extract text from a YouTube URL or video ID, or (5) mentions yt-dlp, YouTube transcript, or video subtitles.
validated-knowledge-synthesis
Transform raw, unorganized information into actionable knowledge through systematic validation. Use when users want to synthesize information from multiple sources (documents, URLs, transcripts, notes) into structured knowledge documents. Supports three document types - curated context (default, optimized for recall), guidance (implementation-focused narrative), and reference (quick lookup). Combines convergent synthesis with tension preservation to maintain productive contradictions. Triggers on requests like "synthesize this information", "create knowledge document from these sources", "transform these notes into actionable guidance", or "help me organize this research".
writing-eval-sloptastic
Quantitative framework for detecting AI-generated "slop" in prose through systematic analysis of structural, lexical, rhetorical, and logical patterns. Use when analyzing text authenticity, evaluating writing quality, detecting AI-generated content, or assessing whether prose has characteristic AI patterns like excessive parallelism, abstraction laddering, chiasmus abuse, platitudes, tautologies, or rhetorical overengineering.