hello-world
ๆจๆถใใใใจใใซไฝฟใในใญใซใใๆจๆถใใฆใใใใใซใกใฏใใชใฉใจ่จใใใใ็บๅใใใ
ๆจๆถใใใใจใใซไฝฟใในใญใซใใๆจๆถใใฆใใใใใซใกใฏใใชใฉใจ่จใใใใ็บๅใใใ
Global hooks for logging Claude Code conversation events to markdown files. Tracks prompts, tool usage, and responses across all sessions. Useful for debugging, auditing, and providing conversation context to Claude.
Session lifecycle management for autonomous coding. Use when starting sessions, resuming work, detecting session type (init vs continue), or managing auto-continuation between sessions.
ๅพ YouTubeใApple Podcast ๆ Bilibili ็ URL ็ฒๅ้ๅญ็จฟใ ็ถไฝฟ็จ่ ่ฒผไธๅฝฑ็ๆ podcast ้ฃ็ต๏ผๆ่ชชใๅนซๆๆฟ้ๅญ็จฟใใ่ฝๆๆๅญใๆ่งธ็ผใ ไฝฟ็จ aits ๅฝไปค็ฒๅๅ งๅฎน๏ผๅๅณ็ตฆไฝฟ็จ่ ๅพ็บไฝฟ็จใ
Helps IDE agents navigate and operate the MOVA Skills Lab: read the registry, plan skill runs and manage episodes.
Expert prompt engineering for LLM applications including prompt design, optimization, RAG systems, agent architectures, and AI product development.
When working with JSON data in LLM prompts (especially large arrays or tabular data), consider the token-efficient TOON (Token-Oriented Object Notation) format which reduces tokens by 30-70% while maintaining lossless JSON representation and structural validation. Use for reading/writing .toon files, converting JSONโTOON, or optimizing structured data for LLM consumption with guardrails like [N] counts and {field} headers.
Manage and compact context for long sessions. Use when context is filling up, creating handoff summaries, optimizing context usage, or preparing for session continuation.
ๆบ่ฝ Prompt ไผๅ้กพ้ฎๆ่ฝใๅบไบ Anthropic ๅฎๆนๆไฝณๅฎ่ทต,้่ฟๅบๆฏ่ฏๅซๅๆๆฏๅน้ ,ๅฐ็จๆท็ๆจก็ณ้ๆฑ่ฝฌๅไธบ้ซ่ดจ้ promptใ่งฆๅๅบๆฏ:(1) ็จๆทๆ็กฎ่ฏทๆฑ"ไผๅ prompt"ใ"ๅธฎๆๅ prompt"ใ"ๆน่ฟ่ฟไธชๆไปค";(2) ็จๆท็้ๆฑๆ่ฟฐๆจก็ณใไธๆธ ๆฐใ็ผบๅฐๅ ณ้ฎไฟกๆฏ;(3) ็จๆทๆๅฐ"ไธ็ฅ้ๆไน่กจ่พพ"ใ"ๆๆไธๅฅฝ"็ญ้ฎ้ขใ้็จไบๆๆ้่ฆไธ Claude ไบคไบ็ๅบๆฏ,้่ฟ็ปๆๅๅฏน่ฏๆๆ้ๆฑ,็ๆ็ฌฆๅ Claude 4.5 ๆไฝณๅฎ่ทต็ไผๅ promptใ
Suno็จใฎBGMใใญใณใใใ็ๆใใYouTubeใซใขใใใญใผใใใใใใฎAgent skill
Orchestrate reliable multi-agent reasoning using MAKER (Maximal Agentic Knowledge Engine for Reasoning). Implements three-pillar architecture for transforming probabilistic LLM outputs into deterministic, verifiable results. Use when tasks require high reliability, parallel consensus voting, or systematic error detection. Triggers include reliability-critical tasks, multi-step reasoning chains, consensus-based verification, parallel agent execution, or explicit MAKER invocation.
[11] CONTINUE. Resume an existing session. Use when continuing previous work to load AGENTS.md, MEMORY.md, and the chosen session log, then confirm readiness.
Debug OpenAI/Gemini image generation failures for Sketch Magic. Use when `/api/convert` returns 500, when models are unsupported, when outputs are empty, or when provider timeouts/quota errors appear.
LangChain implementation patterns with templates, scripts, and examples for RAG pipelines
Interact with TextCleaner's REPL interface to manage pipelines, set input text, and process data through the socket server
Search through historical Claude sessions for code, conversations, and commands. Use when user asks about previous sessions, past conversations, "did I ever", "find in history", or wants to retrieve code/info from earlier chats.
Auto-loaded at session start via SessionStart hook. Teaches skill invocation protocol, tool selection rules (look-at for media, skills for workflows), agent delegation patterns, and enforcement mechanisms. NOT user-triggered - provides foundational skill usage discipline for all sessions.
Use when Codex needs curated documentation context or outlines from the Context7 MCP server.
This skill should be used when the user asks "what is LoRA", "compare models", "which model is best for Chinese", "SFT vs DPO", "how to handle overfitting", "class imbalance solution", "model architecture", "training method comparison", or needs reference information about LLM fine-tuning. Provides structured knowledge base for models, methods, architectures, and troubleshooting.
Creates new specialist subagents based on detected tech stack or observed patterns. Use proactively during /claudenv to create agents for detected technologies, or when usage patterns suggest a new specialist is needed. Similar to meta-skill but for agents.
Agent Lightning๋ฅผ ์ฌ์ฉํ์ฌ AI ์์ด์ ํธ๋ฅผ ์๋์ผ๋ก ์ต์ ํํ๋ ๋ฐฉ๋ฒ์ ์ ๊ณตํฉ๋๋ค.