SKILL.md files package domain expertise into something any AI agent can use. Drop one into your project and your agent learns how to process PDFs, design interfaces, write tests, or whatever the skill teaches.
1396 skills
Use when the user explicitly asks for a desktop or system screenshot (full screen, specific app or window, or a pixel region), or when tool-specific capture capabilities are unavailable and an OS-level capture is needed.
This skill should be used when the user asks to "escalate privileges on Linux", "find privesc vectors on Linux systems", "exploit sudo misconfigurations", "abuse SUID binaries", "exploit cron jobs for root access", "enumerate Linux systems for privilege escalation", or "gain root access from low-privilege shell". It provides comprehensive techniques for identifying and exploiting privilege escalation paths on Linux systems.
Resolves a PostHog experiment reference from natural language to a concrete experiment ID by browsing `experiment-list` (not feature-flag tools), with disambiguation when multiple experiments match. Use when the user names or quotes an experiment ("split test demo", "the File engagement boost experiment", "onboarding retention test", "landing page hero experiment", "pricing experiment"), describes it loosely ("the signup experiment", "my pricing test", "the one with the new checkout"), uses a...
[Extended thinking: This workflow implements a sophisticated debugging and resolution pipeline that leverages AI-assisted debugging tools and observability platforms to systematically diagnose and res
A collection of PostHog skills for enhancing AI-assisted workflows. Add this repo as a Claude Code plugin marketplace to get access to all PostHog skills: Then install individual plugins: Or browse available plugins: Copy any skill directory to .claude/skills/ in your project: Any directory under skills/ that contains a .claude-plugin/plugin.json is automatically discovered and added to the market
Master on-call shift handoffs with context transfer, escalation procedures, and documentation. Use when transitioning on-call responsibilities, documenting shift summaries, or improving on-call processes.
A collection of PostHog skills for enhancing AI-assisted workflows. Add this repo as a Claude Code plugin marketplace to get access to all PostHog skills: Then install individual plugins: Or browse available plugins: Copy any skill directory to .claude/skills/ in your project: Any directory under skills/ that contains a .claude-plugin/plugin.json is automatically discovered and added to the market
This skill should be used when the user asks to "test API security", "fuzz APIs", "find IDOR vulnerabilities", "test REST API", "test GraphQL", "API penetration testing", "bug bounty API testing", or needs guidance on API security assessment techniques.
A comprehensive Model Context Protocol (MCP) server for Notion integration with enhanced functionality, robust error handling, production-ready features, and bulletproof validation. - ✅ Search: Find pages and databases with advanced filtering - ✅ Page Operations: Create, read, update pages with full content support - ✅ Content Management: Add paragraphs, headings, bullet points, todos, links, and
Your AI forgets everything when you close the tab. Phloem fixes that. Phloem is a local MCP server that gives your AI persistent memory across sessions. It works with any tool that supports the Model Context Protocol — an open standard. Today that includes Claude Code, VS Code, Cursor, Windsurf, Zed, Neovim, Cline, Warp, Continue, JetBrains, and more arriving every week. You install it once. Every
MCP (Model Context Protocol) server for RAGStack knowledge bases. Enables AI assistants to search, chat, upload documents/media, and scrape your knowledge base. Get your GraphQL endpoint and API key from the RAGStack dashboard: Settings → API Key Edit ~/Library/Application Support/Claude/claudedesktopconfig.json (Mac) or %APPDATA%\Claude\claudedesktopconfig.json (Windows): Edit ~/.aws/amazonq/mcp.
Combine vector and keyword search for improved retrieval. Use when implementing RAG systems, building search engines, or when neither approach alone provides sufficient recall.
Connect Open Data to LLMs in minutes! We enable 2 things: Open Data Access: Access to many public datasets right from your LLM application (starting with Claude, more to come). Publishing: Get community help and a distribution network to distribute your Open Data. Get everyone to use it! How do we do that? Access: Setup our MCP servers in your LLM application in 2 clicks via our CLI tool (starting
An MCP server that triangulates customer support tickets and feature requests to help PMs decide what to build next. - Signal triangulation — Not just data access. Matches support tickets against feature requests to find convergent themes, then scores them with a weighted formula that gives convergent signals a 2x priority boost. - Composability — Designed to work with other MCP servers. Pass chur
Zero-hallucination answers • Gemini Deep Research • 14 Security Layers • Enterprise Compliance What's New 2026 • Deep Research • Document API • Create Notebooks • Security • Install - 🔍 Query your NotebookLM notebooks — source-grounded, zero-hallucination answers - 📚 Create & manage notebooks programmatically — no manual clicking - 🎙️ Generate audio overviews — podcast-style summaries of your d
Production-ready Rust SDK for the Model Context Protocol (MCP) with zero-boilerplate development and progressive enhancement. Build MCP servers in seconds with automatic schema generation, type-safe handlers, and multiple transport protocols. - Rust 1.89.0+ (Edition 2024) - Check with rustc --version - Tokio async runtime Add to your Cargo.toml: Or with cargo: TurboMCP uses feature flags for progr
MetaMCP is a MCP proxy that lets you dynamically aggregate MCP servers into a unified MCP server, and apply middlewares. MetaMCP itself is a MCP server so it can be easily plugged into ANY MCP clients. For more details, consider visiting our documentation site: https://docs.metamcp.com English | 中文 - 🎯 Use Cases - 📖 Concepts - 🖥️ MCP Server - 🔐 Environment Variables \& Secrets (STDIO MCP Serve
A collection of PostHog skills for enhancing AI-assisted workflows. Add this repo as a Claude Code plugin marketplace to get access to all PostHog skills: Then install individual plugins: Or browse available plugins: Copy any skill directory to .claude/skills/ in your project: Any directory under skills/ that contains a .claude-plugin/plugin.json is automatically discovered and added to the market
Design multi-cloud architectures using a decision framework to select and integrate services across AWS, Azure, and GCP. Use when building multi-cloud systems, avoiding vendor lock-in, or leveraging best-of-breed services from multiple providers.
Required reading before writing any HogQL/SQL or calling execute-sql against PostHog. Use whenever the user wants to search, find, or do complex aggregations PostHog entities (insights, dashboards, cohorts, feature flags, experiments, surveys, hog flows, data warehouse, persons, etc.) and query analytics data (trends, funnels, retention, lifecycle, paths, stickiness, web analytics, error tracking, logs, sessions, LLM traces).
Multi-agent AI consultation framework for Claude Code via MCP. Get a second (and third) opinion from other LLMs when Claude Code alone isn't enough. Claude Code is powerful, but one brain can miss bugs, overlook edge cases, or get stuck in a local optimum. Critical decisions benefit from diverse perspectives. Concilium runs parallel consultations with multiple LLMs through standard MCP protocol. E
NOTICE: claude code is available with Anthropic's $20/mo subscription, so I consider codemcp fully obsolete. However, there are some good design ideas (especially around the Git-versioning scheme) that I eventually want to port into the current generation of agentic coding clis. Make Claude Desktop a pair programming assistant by installing codemcp. With it, you can directly ask Claude to implemen
This project implements a sophisticated multi-agent research system based on the concepts described in Anthropic's article: Building a Multi-Agent Research System. The system leverages the power of coordinated AI agents to handle deep and complex research queries that require multiple perspectives and iterative investigation. The system is built around a Lead Research Agent that orchestrates the e