INVOKE THIS SKILL at the START of any LangChain/LangGraph/Deep Agents project, before writing any agent code. Determines which framework layer is right for the task: LangChain, LangGraph, Deep Agents, or a combination. Must be consulted before other agent skills.
An image-analysis workflow that combines Gemini's vision model with extended reasoning and code execution. It can inspect an image and then write and run code to produce the requested result.
A skill for analyzing videos with Google's Gemini 3 video-understanding API. It accepts YouTube links and common local video files, then can summarize them or extract structured information, chapters, timestamps, and answers about their content.
Call Google Gemini CLI from within Claude Code to leverage Gemini models for cross-checking, web search integration, or alternative perspectives. This skill should be used when the user requests to use Gemini or Google AI from within Claude Code, or when cross-validation with another AI is needed. Triggers include…
A version-control workflow that stores text files in Git and synchronizes non-text files through Hugging Face Hub, an online service for storing files and datasets. It also defines rules for initializing repositories and making commits.
A workflow for using Git worktrees to give multiple Claude Code sessions separate folders and branches. A worktree is an additional working directory linked to the same Git repository.
Turn any folder of files into a navigable knowledge graph with community detection, an honest audit trail, and three outputs: interactive HTML, GraphRAG-ready JSON, and a plain-language GRAPHREPORT.md.
Create and configure Claude Code hooks for customizing agent behavior. Use when the user wants to (1) create a new hook, (2) configure automatic formatting, logging, or notifications, (3) add file protection or custom permissions, (4) set up pre/post tool execution actions, or (5) asks about hook events like…
Create and edit JSON Canvas files (.canvas) with nodes, edges, groups, and connections. Use when working with .canvas files, creating visual canvases, mind maps, flowcharts, or when the user mentions Canvas files in Obsidian.
INVOKE THIS SKILL when setting up a new project or when asked about package versions, installation, or dependency management for LangChain, LangGraph, LangSmith, or Deep Agents. Covers required packages, minimum versions, environment requirements, versioning best practices, and common community tool packages for both…
INVOKE THIS SKILL when you need human-in-the-loop approval, custom middleware, or structured output. Covers HumanInTheLoopMiddleware for human approval of dangerous tool calls, creating custom middleware with hooks, Command resume patterns, and structured output with Pydantic/Zod.
INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. Covers document loaders, RecursiveCharacterTextSplitter, embeddings (OpenAI), and vector stores (Chroma, FAISS, Pinecone).
INVOKE THIS SKILL when writing ANY LangGraph code. Covers StateGraph, state schemas, nodes, edges, Command, Send, invoke, streaming, and error handling.
INVOKE THIS SKILL when implementing human-in-the-loop patterns, pausing for approval, or handling errors in LangGraph. Covers interrupt(), Command(resume=...), approval/validation workflows, and the 4-tier error handling strategy.
INVOKE THIS SKILL when your LangGraph needs to persist state, remember conversations, travel through history, or configure subgraph checkpointer scoping. Covers checkpointers, threadid, time travel, Store, and subgraph persistence modes.
INVOKE THIS SKILL when creating evaluation datasets, uploading datasets to LangSmith, or managing existing datasets. Covers dataset types (finalresponse, singlestep, trajectory, RAG), CLI management commands, SDK-based creation, and example management. Uses the langsmith CLI tool.
INVOKE THIS SKILL when building evaluation pipelines for LangSmith. Covers three core components: (1) Creating Evaluators - LLM-as-Judge, custom code; (2) Defining Run Functions - how to capture outputs and trajectories from your agent; (3) Running Evaluations - locally with evaluate() or auto-run via LangSmith. Uses…
INVOKE THIS SKILL when working with LangSmith tracing OR querying traces. Covers adding tracing to applications and querying/exporting trace data. Uses the langsmith CLI tool.
Manage macOS Finder color tags on files and directories. This skill should be used when users want to add, change, remove, or search for files by color tags (빨간색/Red, 파란색/Blue, etc.), check current tags, or organize files with color coding. Common triggers include "빨간색 태그 달아줘", "파란색으로 바꿔줘", "태그 제거해줘", or "빨간색 파일들 찾아줘".