Markdown AI Agent Skills

skill-depot replaces the "dump all skill frontmatter into context" approach with selective, semantic retrieval. Agent skills are stored as Markdown files and indexed with vector embeddings — only the relevant skills are loaded when needed, keeping context lean. - Semantic Search — Find skills by meaning, not just keywords, using embedded vector search - Fully Local — No API keys, no cloud. U

Provides score interpretation (< 0.3 good, > 0.5 skip), query optimization, and source naming for query_documents, ingest_file, ingest_data tools. Use this skill when working with RAG, searching documents, ingesting files, saving web content, or handling PDF, HTML, DOCX, TXT, Markdown.

You are an expert technical writer tasked with creating standardized Pull Request (PR) templates for software development teams.

A Model Context Protocol (MCP) server that provides a comprehensive API for managing todo items. - Create todos: Add new tasks with title and markdown description - Update todos: Modify existing tasks - Complete todos: Mark tasks as done - Delete todos: Remove tasks from the list - Search todos: Find tasks by title or creation date - Summarize todos: Get a quick overview of active tasks This MCP s

TL;DR for AI agents — enquire-mcp is the 1 Obsidian MCP: a local memory and document-intelligence layer that makes one vault persistently searchable from Claude Code, Claude Desktop, Cursor, ChatGPT, Codex, OpenClaw, and any MCP client. It returns cited source context across Markdown, PDFs + OCR, Canva

This MCP server provides functionality to fetch web content in various formats, including HTML, JSON, plain text, and Markdown. Available on NPM - fetchhtml - Fetch a website and return the content as HTML - url (string, required): URL of the website to fetch - headers (object, optional): Custom headers to include in the request - maxlength (number, optional): Maximum length to fetch (default 5000

通过 uvx 安装并运行： 安装完成后，直接运行： 运行后你可以直接使用工具，例如： 或（如果是 uvx 安装）： 好的，这是转换后的 Markdown 版本： 好的，这是转换后的 Markdown 版本： 1. 配置环境变量（可选） 你可以通过 .env 文件或系统环境变量配置 DolphinDB 的连接信息： 也可以不设置，系统将使用默认值。 该命令会启动 MCP 插件服务，供外部调用。 3. FastMCP Agent 使用示例 启动后，你的工具将通过 FastMCP 对外暴露以下函数接口： listtbs(dbName: str) querytablediskusage(database: str, tableName: str) querydolphindb(script: str) 可通过 MCP 前端界面或对接 LLM 工具链来进行访问。

An MCP server that provides real-time whale alerts on Hyperliquid, flagging positions with a notional value exceeding $1 million. - Tool: getwhalealerts: Fetches recent whale transactions and returns them as a Markdown table using pandas for clean formatting. - Prompt: summarizewhaleactivity: Generates a summary of whale transactions, including metrics like total position value and notable symbols

A collection of AI agents for various tasks. Welcome to the agents repository! This project contains various AI agent definitions. The definitions can be used by any agentic system that supports markdown. An MCP (Model Context Protocol) server that delivers AI agent instructions on demand from this repository's collection of 42+ specialized agents. The server exposes 3 MCP tools: List all availabl