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.
1414 skills
Per-component i18n AI-powered translation. Visual Editor. Multilingual CMS. React + Vite • Most i18n libraries are either too complex, too rigid, or not built for modern frameworks. Intlayer is a modern i18n solution for web and mobile apps. It’s framework-agnostic, AI-powered, and includes a free CMS & visual editor. With per-locale content files, TypeScript autocompletion, tree-shakable dictiona
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
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
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
BrowserAct Skills Browser automation CLI built for AI agents. Get past anti-bot walls, hand off to humans across platforms when stuck, run parallel tasks without cross-contamination, and isolate multiple accounts in independent browsers. The browser an AI agent needs has to reach places standard tools can't, let a human seamlessly take over when the agent is stuck, keep parallel tasks from cross-c
Analyze a repository to generate recommended Claude Code settings.json permissions. Use when setting up a new project, auditing existing settings, or determining which read-only bash commands to allow. Detects tech stack, build tools, and monorepo structure.
Optimize Bazel builds for large-scale monorepos. Use when configuring Bazel, implementing remote execution, or optimizing build performance for enterprise codebases.
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
GitHub patterns using gh CLI for pull requests, stacked PRs, code review, branching strategies, and repository automation. Use when working with GitHub PRs, merging strategies, or repository management tasks.
"Not a browser for humans that AI can use. A browser built for AI that humans can watch." Quick Start • Benchmarks • Architecture • Security • Documentation Traditional browsers (Chrome, Firefox) and automation tools (Playwright, Selenium) were built for human retinas and pixels. Treating a web page as an XML document or an Accessibility Tree is the wrong abstraction for intelligence. Axon is enti
A task management system built for AI agents. Official website: https://claudiacli.com/ Claudia provides structured task tracking with a Model Context Protocol (MCP) server, enabling AI assistants like Claude to manage their own work through hierarchical tasks, dependencies, sprints, and acceptance criteria verification. AI agents need a way to: - Track progress across complex, multi-step tasks -
Handle errors as values using fp-ts Either and TaskEither for cleaner, more predictable TypeScript code. Use when implementing error handling patterns with fp-ts.
Modern Angular UI patterns for loading states, error handling, and data display. Use when building UI components, handling async data, or managing component states.
Vexor is a semantic search engine that builds reusable indexes over files and code. It supports configurable embedding and reranking providers, and exposes the same core through a Python API, a CLI tool, and an optional desktop frontend. Vexor Demo Video Vexor has been recognized and featured by the community: - Ruan Yifeng's Weekly (Issue 379) - A leading tech newsletter in the Chinese developer
Master enterprise-grade Scala development with functional
Automate ClickUp project management including tasks, spaces, folders, lists, comments, and team operations via Rube MCP (Composio). Always search tools first for current schemas.
cache.overflow AI agents sharing knowledge with AI agents Your coding agent spends 10 minutes solving a problem. Another agent somewhere hits the same issue—solves it instantly. That's cache.overflow: a knowledge marketplace where AI agents learn from each other, making every problem cheaper to solve the second time around. - Earn passive income - Publish solutions once, earn tokens every time ano
Guide for quality focused software architecture. This skill should be used when users want to write code, design architecture, analyze code, in any case that relates to software development.
Self-improving tool discovery for AI agents. Install one MCP server. Your agent finds the rest. npm · GitHub · Contributing Forage is an MCP server that lets AI agents discover, install, and learn to use new tools — automatically. When an agent hits a wall, it forages for the right tool, installs it, and teaches itself how to use it. No restarts. No manual config. The agent gets permanently smarte
Analyze Rails apps and provide upgrade assessments
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