jc-baseline-v2-1-eval
Execute Joseph Cognitive Baseline v2.1 evaluation protocol.
Execute Joseph Cognitive Baseline v2.1 evaluation protocol.
Run different AI agent CLIs and orchestrate them for complex tasks or alternative approaches or opinions.
Build production-ready MCP clients in TypeScript or Python. Handles connection lifecycle, transport abstraction, tool orchestration, security, and error handling. Use for integrating LLM applications with MCP servers.
Configure Home Assistant Assist voice control with pipelines, intents, wake words, and speech processing. Use when setting up voice control, creating custom intents, configuring TTS/STT, or building voice satellites. Activates on keywords: Assist, voice control, wake word, intent, sentence, TTS, STT, Piper, Whisper, Wyoming.
Implement ML pipelines, model serving, and feature engineering. Handles TensorFlow/PyTorch deployment, A/B testing, and monitoring. Use PROACTIVELY for ML model integration or production deployment.
Common reasoning protocol shared across all subagents.
Update fx-cc plugin agents, skills, or commands based on conversation learnings. Use when the user says "use /learn to...", "learn to...", "remember to...", "don't do X again", or when an agent/skill misbehaved and needs correction. This skill modifies plugin source files but does NOT commit changes - they require manual review before committing.
AIใณใผใใฃใณใฐๆฏๆดใใผใซใฎใณใณใใญในใใใกใคใซ๏ผCLAUDE.md็ญ๏ผใๆ้ฉๅใใในใญใซใ ไปฅไธใฎ็ถๆณใงไฝฟ็จ: (1) ใฆใผใถใผใใCLAUDE.mdใๆนๅใใฆใใใณใณใใญในใใใกใคใซใๆ้ฉๅใใฆใใจไพ้ ผใใๆ (2) ใฆใผใถใผใๆ็คบ็ใซใ/ai-contextใใๅฎ่กใใๆ-optimizer (3) AIๅใใใญใฅใกใณใใฎๅ่ณชๆนๅใๆฑใใใใๆ
LLM ๋ชจ๋ธ ์๋ ์ ๋ฐ์ดํธ ์์คํ - ํญ์ ์ต์ ๋ชจ๋ธ ์ ๋ณด ์ ์ง
ๅๅปบๅ ทๆ่ชๅฎไน็ณป็ปๆ็คบๅๅทฅๅ ท้ ็ฝฎ็ไธไธๅ Claude Code ๅญไปฃ็ใๅฝ็จๆท่ฆๆฑๅๅปบๆฐ็ๅญไปฃ็ใ่ชๅฎไนไปฃ็ใไธไธๅฉๆ๏ผๆไธบ Claude Code ้ ็ฝฎ็นๅฎไปปๅก็ AI ๅทฅไฝๆตๆถไฝฟ็จใ
Expert knowledge for Technology Layer modeling in Documentation Robotics
Autonomous homelab operations using OODA loop (Observe, Orient, Decide, Act) - use when reviewing system state, planning autonomous actions, or investigating operational issues
Use when creating new skills or editing existing skills - applies prompt engineering principles to write clear, goal-focused process documentation that trusts LLM intelligence
Expert knowledge for Motivation Layer modeling in Documentation Robotics
This skill should be used when the user asks to "create MCP server", "add MCP tools", "implement FastMCP endpoints", "expose MCP resources", "configure MCP servers", or mentions Model Context Protocol, tool schemas, or MCP integration patterns.
Train task-specific small language models (SLMs) using the Distil Labs CLI. Helps with data preparation, model training, and deployment.
่ซๆใฎใใฌใผใณใใญในใใ่ชญใฟ่พผใฟใใฆใผใถใผใฎ่ณชๅใซ็ ็ฉถใฎใใญใจใใฆๅใใใใใๅ็ญใใในใญใซใใฆใผใถใผใใใใฎ่ซๆใซใคใใฆ่ณชๅใใ่ซๆใฎๅ ๅฎนใๆใใฆใใใใฎ็ ็ฉถใฎ็ฎ็ใฏ๏ผใใชใฉใจๆ็คบใใๆใซไฝฟ็จใClaude่ช่บซใ็ดๆฅๅ็ญใใใ
็จไบๅๅปบๆๆๆ่ฝ็ๆๅใๅฝ็จๆทๆณ่ฆๅๅปบๆฐๆ่ฝ๏ผๆๆดๆฐ็ฐๆๆ่ฝ๏ผไปฅ้่ฟไธไธ็ฅ่ฏใๅทฅไฝๆต็จๆๅทฅๅ ท้ๆๆฉๅฑ Claude ็่ฝๅๆถ๏ผๅบไฝฟ็จๆญคๆ่ฝใ
Use when starting any conversation - establishes mandatory workflows for finding and using skills, including using Skill tool before announcing usage, following brainstorming before coding, and creating TodoWrite todos for checklists
Explain what FAF is, why it matters, and how it works when user asks about FAF, project context, AI-readiness, The Reading Order, or persistent context. Use when user says "what is FAF", "explain project.faf", "why do I need this", "how does AI context work", or shows confusion about persistent context. Teaches foundational concepts before recommending specific actions.