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Found 106 Skills
This skill should be used when the user asks to "build an MCP server", "create an MCP tool", "expose resources with MCP", "write an MCP client", or needs guidance on the Model Context Protocol Python SDK best practices, transports, server primitives, or LLM context integration.
A minimal teaching framework for understanding AI Agent architecture with core loop, fake LLM interface, and skill discovery system
Control and automate real browser sessions through CDP, preserving login state and cookies for LLM-driven interactions
Build AI agents with in-process agent loops using Anthropic or OpenAI APIs, custom tools, MCP servers, and multi-turn conversations
OpenClaw Chinese localized AI assistant platform with CLI, dashboard, multi-platform chat integration (WhatsApp/Telegram/Discord), and LLM provider support
Use the mm CLI to index, explore, query, and extract content from multimodal directories containing images, videos, PDFs, code, and other files. Triggers: exploring a directory's contents, listing/finding files by type or size, extracting text from PDFs, getting image metadata, searching across file contents, counting tokens, viewing directory trees, extracting PDF page mosaics, video keyframe extraction, 'what files are in this folder', 'find all images', 'show me the PDFs', 'how much storage do videos use', 'extract text from this PDF', 'search documents for X', 'analyze this directory', 'how many tokens', 'show the tree'.
Consult external LLMs (Gemini, OpenAI/Codex, Qwen) for second opinions, alternative plans, independent reviews, or delegated tasks. Use when a user asks for another model's perspective, wants to compare answers, or requests delegating a subtask to Gemini/Codex/Qwen.
企业微信客服自动化系统。自动同意好友添加、基于知识库的智能问答、未知问题人工介入提醒。适用于企业微信客服场景的 AI 助手机器人。
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Persistent memory layer for AI agents using Postgres/pgvector with MCP server support
Control web interfaces with natural language using Page Agent, a JavaScript in-page GUI agent for browser automation
Add persistent learning and self-improvement to AI agents using ACE framework