Your agent can do more. Find the skill that makes it happen.
Find your next superpower If you are an agent, refer to our llms.txt for full access.Guides landing page design for startups, product pages, and SaaS marketing. Covers above-the-fold layout, hero sections, CTA psychology, social proof placement, mobile design, and F-pattern reading to support conversion optimization.
Combines visual design with proven conversion elements using an 11-element framework. Creates landing pages in Next.js 14+ and ShadCN UI with an emphasis on memorable aesthetics.
Read-only queue dashboard for workspace-aware ship. (gstack)
Covers LLM application architecture using LangChain 1.x and LangGraph. Supports AI agent implementation, memory management, tool integration, and complex LLM workflows.
Covers project dependencies for LangChain, LangGraph, LangSmith, and Deep Agents. Includes required packages, minimum versions, environment requirements, versioning practices, and community tool packages for Python and TypeScript.
Builds LangChain agents with create_agent and custom tools. Covers middleware for human-in-the-loop interactions and error handling.
Covers HumanInTheLoopMiddleware for approving dangerous tool calls and custom middleware hooks. Includes Command resume patterns and structured output with Pydantic or Zod.
Follows the official quickstart to scaffold a minimal LangChain agent in Python. Supports quickly building or trying an agent locally.
Covers retrieval-augmented generation using document loaders, RecursiveCharacterTextSplitter, and OpenAI embeddings. Includes Chroma, FAISS, and Pinecone vector stores.
Follows the official quickstart to scaffold a minimal LangChain agent in TypeScript. Supports quickly building or trying an agent locally.
Provides declarative LangChain4j AI service patterns using interfaces and annotations. Supports Java LLM integration, conversational memory, chatbot development, and agents with tool integration and function calling.
Provides LangChain4j patterns for implementing MCP servers and Java AI tools. Covers tool calling, MCP client integration with AI services, and securing tool exposure in agent workflows.
Skills give your agent reusable instructions for a specific job. Pick one, read what it does, and bring it into your workflow.
A name only tells half the story. Search the full description and instructions to find the right fit.
Read the skill, visit its source, and see exactly what you’re adding to your agent.
Copy the install command from a skill page and run it in your project.
npx skillycli add owner/repo --skill name