Train machine learning models with automated workflows. Analyzes datasets, selects model types (classification, regression), configures parameters, trains with cross-validation, and saves model artifacts. Use when asked to "train model" or "evalua...
Sage Agent 执行引擎开发指南，涵盖 UnifiedExecutor、Subagent、Lifecycle 管理
Production-grade agentic system development with LlamaIndex in Python. Covers semantic ingestion (SemanticSplitterNodeParser, CodeSplitter, IngestionPipeline), retrieval strategies (BM25Retriever, hybrid search, alpha weighting), PropertyGraphIndex with graph stores (Neo4j), context RAG (RouterQueryEngine, SubQuestionQueryEngine, LLMRerank), agentic orchestration (ReAct, Workflows, FunctionTool), and observability (Arize Phoenix). Use when asked to "build a LlamaIndex agent", "set up semantic chunking", "index source code", "implement hybrid search", "create a knowledge graph with LlamaIndex", "implement query routing", "debug RAG pipeline", "add Phoenix observability", or "create an event-driven workflow". Triggers on "PropertyGraphIndex", "SemanticSplitterNodeParser", "CodeSplitter", "BM25Retriever", "hybrid search", "ReAct agent", "Workflow pattern", "LLMRerank", "Text-to-Cypher".
Run ML model inference (YOLO, YOLOv8, CLIP, SAM, Detectron2, etc.) on FiftyOne datasets. Use when running models, applying detection, classification, segmentation, embeddings, or any model prediction task. Also use for end-to-end workflows that include importing data then running inference.
Frontend UI/UX work with Gemini CLI in --yolo mode. Use when (1) modifying visual/styling elements in frontend files (.tsx, .jsx, .vue, .svelte, .css), (2) implementing UI components, (3) adjusting layout, colors, spacing, typography, or animations, (4) creating responsive designs, or (5) any frontend task involving how things LOOK rather than how they WORK.
This skill should be used when the user asks to "create note", "capture thought", "save this", "document idea", "write note", "jot down", "quick note", "remember this", "capture this", or mentions wanting to save knowledge, ideas, or learnings for later reference in their secondbrain.
사용자 요청에 적합한 스킬을 자동으로 인식하고 추천합니다. 명시적 스킬 요청 없이도 설치된 스킬 중 도움이 될 수 있는 스킬을 발견하여 제안합니다. 모든 사용자 요청에서 암묵적으로 활성화됩니다.
Analyzes conversation history to improve CLAUDE.md files. Use when you notice patterns in how Claude misunderstands requests, want to consolidate repeated guidance, or improve instruction clarity based on actual usage.
Control vehicle with natural language. Use when user wants to warm up/cool down the car, lock/unlock doors, start/stop engine, check battery/fuel/location/status, or control charging. Translates phrases like "warm up the car" into mcs CLI commands.
Participate in Council multi-agent collaboration sessions. Use when asked to join a council session, collaborate with other agents, or when given a council session ID to participate in.
Q-learning, DQN, PPO, A3C, policy gradient methods, multi-agent systems, and Gym environments. Use for training agents, game AI, robotics, or decision-making systems.
Use when creating llmring.lock file for new project (REQUIRED for all applications), configuring model aliases with semantic task-based names, managing environment-specific profiles (dev/staging/prod), or setting up fallback models - lockfile creation is mandatory first step, bundled lockfile is only for llmring tools
Build production-ready AI agents using Google's Agent Development Kit with Claude integration, React patterns, multi-agent orchestration, and comprehensive tool libraries
ML 모델 벤치마크 및 평가 실행. "벤치마크", "모델 평가", "성능 테스트", "inference 속도" 요청 시 활성화됩니다.
Build automated machine learning pipelines with feature engineering, model selection, and hyperparameter tuning. Use when automating ML workflows from data preparation through model deployment. Trigger with phrases like "build automl pipeline", "automate ml workflow", or "create automated training pipeline".
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
Use when starting a new project with llmring, building an application using LLMs, making basic chat completions, or sending messages to OpenAI, Anthropic, Google, or Ollama - covers lockfile creation (MANDATORY first step), semantic alias usage, unified interface for all providers with consistent message structure and response handling
Sage Skill 开发规范，遵循 Agent Skills 开放标准，兼容 Claude Code 格式
Expert guidance for crafting effective LLM prompts using proven techniques like chain-of-thought and few-shot learning
