RADAR SKILL · GITHUB
Agent Skills utili ordinati per utilizzo reale
Confronta Skills verificati per funzione, contenuto del pacchetto, installazioni e affidabilità della fonte.
- AMBITO CATALOGO
- VERIFICATO
- Skills
- 15.628
- repository
- 2528
- ultimo aggiornamento
- 12 ott 2026
hkudscli-anything-n8n
- Command-line interface for n8n workflow automation platform. Manages workflows, executions, credentials, variables, and tags. Based on n8n Public API v1.1.1 (n8n = 1.0.0).
- installazioni
- 6
- GitHub Stars
- 49,1K
- Aggiornato
- 21 ago
hkudscli-anything-pm2
- Command-line interface for PM2 - A stateless CLI for Node.js process management via the PM2 CLI. List, start, stop, restart processes, view logs, and manage system configuration.
- installazioni
- 6
- GitHub Stars
- 49,1K
- Aggiornato
- 21 ago
styleofagent-browser
Browser automation for AI agents via inference.sh. Navigate web pages, interact with elements using @e refs, take screenshots, record video. Capabilities: web scraping, form filling, clicking, typing, drag-drop, file upload, JavaScript execution. Use for: web automation, data extraction, testing, agent browsing, research. Triggers: browser, web automation, scrape, navigate, click, fill form, screenshot, browse web, playwright, headless browser, web agent, surf internet, record video
- installazioni
- 6
- GitHub Stars
- 0
- Aggiornato
- 2 set
styleofhappyhorse
Generate and edit videos with Alibaba HappyHorse 1.0 models via inference.sh CLI. Models: HappyHorse T2V, I2V, R2V, Video Edit. Capabilities: text-to-video, image-to-video, reference-to-video, video editing with natural language, character preservation, 720P/1080P, up to 15 seconds. Use for: physically realistic video, video editing, character-consistent content, product demos, social media. Triggers: happyhorse, happy horse, alibaba video, happyhorse 1.0, dashscope video, alibaba happyhorse, vi
- installazioni
- 6
- GitHub Stars
- 0
- Aggiornato
- 2 set
langchain-aideep-agents-core
INVOKE THIS SKILL when building ANY Deep Agents application. Covers createdeepagent(), harness architecture, SKILL.md format, and configuration options.
- installazioni
- 5
- GitHub Stars
- 1,3K
- Aggiornato
- 8 ott
langchain-aideep-agents-orchestration
INVOKE THIS SKILL when using subagents, task planning, or human approval in Deep Agents. Covers SubAgentMiddleware, TodoList for planning, and HITL interrupts.
- installazioni
- 5
- GitHub Stars
- 1,3K
- Aggiornato
- 8 ott
langchain-aideepagents-python-quickstart
Scaffold a minimal local Deep Agent in Python by following the official quickstart, using provider-native web search instead of Tavily. Use when the user wants to quickly build or try a Deep Agent locally.
- installazioni
- 5
- GitHub Stars
- 1,3K
- Aggiornato
- 8 ott
langchain-aideepagents-typescript-quickstart
Scaffold a minimal local Deep Agent in TypeScript by following the official quickstart, using provider-native web search instead of Tavily. Use when the user wants to quickly build or try a Deep Agent locally.
- installazioni
- 5
- GitHub Stars
- 1,3K
- Aggiornato
- 8 ott
langchain-aiecosystem-primer
INVOKE FIRST for any LangChain / LangGraph / Deep Agents agent building project before consulting other skills or writing any agent code. Required starting point for up to date info on framework selection (LangChain vs LangGraph vs Deep Agents vs hybrid composition), agent patterns, install, environment setup, and which skill to load next.
- installazioni
- 5
- GitHub Stars
- 1,3K
- Aggiornato
- 8 ott
langchain-aieval-engineering
Inspect an agent repository and optional traces, interview the user, write reviewed Task Specs, build and audit Harbor tasks, and bootstrap reusable project World Knowledge Skills. Use for agent evals, benchmark design, Task generation, controlled Environments, synthetic data, Verifiers, Harbor runs, calibration, or continuous benchmark maintenance.
- installazioni
- 5
- GitHub Stars
- 1,3K
- Aggiornato
- 8 ott
langchain-ailangchain-dependencies
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 Python and TypeScript.
- installazioni
- 5
- GitHub Stars
- 1,3K
- Aggiornato
- 8 ott
langchain-ailangchain-fundamentals
Create LangChain agents with createagent, define tools, and use middleware for human-in-the-loop and error handling.
- installazioni
- 5
- GitHub Stars
- 1,3K
- Aggiornato
- 8 ott
langchain-ailangchain-middleware
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.
- installazioni
- 5
- GitHub Stars
- 1,3K
- Aggiornato
- 8 ott
langchain-ailangchain-python-quickstart
Scaffold a minimal local LangChain agent in Python by following the official quickstart. Use when the user wants to quickly build or try a LangChain agent locally.
- installazioni
- 5
- GitHub Stars
- 1,3K
- Aggiornato
- 8 ott
langchain-ailangchain-rag
INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. Covers document loaders, RecursiveCharacterTextSplitter, embeddings (OpenAI), and vector stores (Chroma, FAISS, Pinecone).
- installazioni
- 5
- GitHub Stars
- 1,3K
- Aggiornato
- 8 ott
langchain-ailangchain-typescript-quickstart
Scaffold a minimal local LangChain agent in TypeScript by following the official quickstart. Use when the user wants to quickly build or try a LangChain agent locally.
- installazioni
- 5
- GitHub Stars
- 1,3K
- Aggiornato
- 8 ott
langchain-ailanggraph-cli
INVOKE THIS SKILL when using the langgraph CLI to scaffold, develop, build, or deploy LangGraph applications. Covers langgraph new, dev, build, up, deploy, and langgraph.json configuration.
- installazioni
- 5
- GitHub Stars
- 1,3K
- Aggiornato
- 8 ott
langchain-ailanggraph-decision-models
INVOKE THIS SKILL when routing a LangGraph agent with a decision model (TypeSafe Jev, SemIf) instead of an LLM, or when auditing an existing agent for LLM calls that only produce a routing decision. Covers langchain-typesafe Noul/Choice/Score, reading answers correctly, threshold design, and LangSmith Gateway wiring.
- installazioni
- 5
- GitHub Stars
- 1,3K
- Aggiornato
- 8 ott
langchain-ailanggraph-fundamentals
INVOKE THIS SKILL when writing ANY LangGraph code. Covers StateGraph, state schemas, nodes, edges, Command, Send, invoke, streaming, and error handling.
- installazioni
- 5
- GitHub Stars
- 1,3K
- Aggiornato
- 8 ott
langchain-ailanggraph-human-in-the-loop
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.
- installazioni
- 5
- GitHub Stars
- 1,3K
- Aggiornato
- 8 ott
langchain-ailanggraph-persistence
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.
- installazioni
- 5
- GitHub Stars
- 1,3K
- Aggiornato
- 8 ott
langchain-ailanggraph-python-quickstart
Scaffold a minimal local LangGraph agent in Python by following the official quickstart. Use when the user wants to quickly build or try a LangGraph agent locally.
- installazioni
- 5
- GitHub Stars
- 1,3K
- Aggiornato
- 8 ott
langchain-ailanggraph-typescript-quickstart
Scaffold a minimal local LangGraph agent in TypeScript by following the official quickstart. Use when the user wants to quickly build or try a LangGraph agent locally.
- installazioni
- 5
- GitHub Stars
- 1,3K
- Aggiornato
- 8 ott
langchain-aimanaged-deep-agents
INVOKE THIS SKILL when building, testing, or deploying Managed Deep Agents in LangSmith. Walks a user through their first agent end to end — interviewing them about what they want to build, mapping it onto what MDA can actually do, then scaffolding and deploying it. Covers the file-based project layout; definedeepagent / defineDeepAgent; instructions, skills, memory, identity, tools, MCP servers, connections, middleware, sandboxes, schedules, channels, and evals; the mda CLI; GitHub deployments;
- installazioni
- 5
- GitHub Stars
- 1,3K
- Aggiornato
- 8 ott