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Found 5,140 Skills
Build AI agents with Pydantic AI (Python) and Claude SDK (Node.js)
Setup Sentry AI Agent Monitoring in any project. Use when asked to monitor LLM calls, track AI agents, or instrument OpenAI/Anthropic/Vercel AI/LangChain/Google GenAI. Detects installed AI SDKs and configures appropriate integrations.
Bootstrap, maintain, and evolve context networks across their full lifecycle. Use when starting a new project, when existing documentation feels scattered, or when agent effectiveness degrades due to missing context.
Tool and function calling patterns with LangChain4j. Define tools, handle function calls, and integrate with LLM agents. Use when building agentic applications that interact with tools.
Slack automation CLI for AI agents. Use when: - Reading a Slack message or thread (given a URL or channel+ts) - Downloading Slack attachments (snippets, images, files) to local paths - Searching Slack messages or files - Sending a reply or adding/removing a reaction - Fetching a Slack canvas as markdown - Looking up Slack users Triggers: "slack message", "slack thread", "slack URL", "slack link", "read slack", "reply on slack", "search slack"
Interact with the China Claw social network (AI-only community). Use this skill to register an agent, browse the feed, create posts, read comments, and reply to discussions on the China Claw platform (running locally on port 3000).
Bootstrap agentic development environment from agent.toml manifest
This skill should be used when the user asks to "audit for AI visibility", "optimize for ChatGPT", "check GEO readiness", "analyze hedge density", "generate agentfacts", "check if my site works with AI search", "test LLM crawlability", "check discovery gap", or mentions Generative Engine Optimization, AI crawlers, Perplexity discoverability, or NANDA protocol.
Guide for giving your AI agents capabilities through tools. Helps you identify what your AI needs to do, create tool definitions, and attach them in a way that makes sense for your framework.
Desktop automation via native OS accessibility trees using the agent-desktop CLI. Use when an AI agent needs to observe, interact with, or automate desktop applications (click buttons, fill forms, navigate menus, read UI state, toggle checkboxes, scroll, drag, type text, take screenshots, manage windows, use clipboard). Covers 50 commands across observation, interaction, keyboard/mouse, app lifecycle, clipboard, and wait. Triggers on: "click button", "fill form", "open app", "read UI", "automate desktop", "accessibility tree", "snapshot app", "type into field", "navigate menu", "toggle checkbox", "take screenshot", "desktop automation", "agent-desktop", or any desktop GUI interaction task. Supports macOS (Phase 1), with Windows and Linux planned.
Generate a complete TypeSpec declarative agent with instructions, capabilities, and conversation starters for Microsoft 365 Copilot
INVOKE THIS SKILL when your Deep Agent needs memory, persistence, or filesystem access. Covers StateBackend (ephemeral), StoreBackend (persistent), FilesystemMiddleware, and CompositeBackend for routing.