Browse 47 tools for your AI coding workflow.
Optimize markdown documentation for LLMs and RAG systems, reducing token consumption by 67-95%.
AGENTS.md rules and skills for AI coding agents, distilled from classic software engineering books.
Up-to-date code documentation for LLMs and AI code editors, eliminating outdated or hallucinated API references.
Official Elastic Agent Skills library for AI coding agents to work with Elasticsearch, Kibana, Observability, and Security.
Convert and sync AI coding-agent rule files between formats with zero dependencies.
Open-source GEO audit engine to optimize websites for AI search visibility and citability.
GitHub Action to automatically fix code formatting and linting issues via autofix.ci.
Local semantic code search engine for AI coding agents, reducing token use and costs by up to 50%.
Complete UI/UX system for Claude Code with 67 specialized agents, design vocabulary, and tested prompts.
CI-native security testing for MCP servers. Attack simulation, schema drift detection, and health scoring before agents depend on them.
Opinionated CLAUDE.md template enforcing software engineering best practices for Claude Code.
Official PHP SDK for building MCP servers and clients, maintained with The PHP Foundation.
A Go-based CLI tool that compiles AI rule templates into target-specific formats for various AI coding assistants.
A unified web extraction and stateful browser automation engine for AI agents, replacing heavy testing frameworks.
Production-grade scaffold with AGENTS.md/SKILL.md, 10-stage DAG pipelines, and cryptographic provenance.
AI agent skill for building modern, composable, and accessible React UI components following the components.build specification.
Specify what you want to build in natural language, and GPT Engineer generates the complete codebase with best practices.
AI-powered SEO content automation agent for trend scouting, competitor analysis, and multilingual article generation.
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM, reducing tokens by 20-95% while preserving answers.
Graph-based tool retrieval for LLM agents, reducing token usage by 79% with 82% accuracy.
