An atelier for your Agent: spec-driven workflows, deep thinking, and code quality.

The definitive guide & configuration system for GitHub Copilot CLI — agents, skills, rules, multi-AI orchestration, and more

A powerful MCP toolkit for coding, providing semantic retrieval and editing capabilities - the IDE for your agent

SkillOpt is a text-space optimizer that trains reusable natural-language skills for frozen LLM agents through trajectory-driven edits, validation-gated updates, and deployable best_skill.md artifacts.

A Model Context Protocol (MCP) server and CLI that provides tools for agent use when working on iOS and macOS projects.

An Agent Skill helping you to optimize Xcode incremental and clean builds by running benchmarks and optimizing build settings.

The MATLAB Agentic Toolkit brings trusted MATLAB capabilities to AI agents, making engineering and scientific workflows agent-ready.

A comprehensive Model Context Protocol (MCP) server that enables AI assistants to control Unreal Engine through the native C++ Automation Bridge plugin. Built with TypeScript and C++.

Agent Skills for Meta Quest/Horizon OS VR Development

Evidence-grounded repository audit CLI - deterministic scanner, MCP server, live dashboard, and a GitHub Action that posts PR diffs.

Agent skill for modern Android development with Jetpack Compose — best practices for code generation and review

MCP server that enables AI agents to perform comprehensive web audits using Google Lighthouse with 13+ tools for performance, accessibility, SEO, and security analysis.

Rails Engine with MCP compliant Spec.

OpenTelemetry skills and reference documentation for AI coding assistants - instrumentation patterns, telemetry quality guides, and Dash0 integration

An MCP server for parallel browser automation by AI agents with multiple cloud providers

🪨 why use many token when few token do trick — Claude Code skill that cuts 65% of tokens by talking like caveman

Peekaboo is a macOS CLI & optional MCP server that enables AI agents to capture screenshots of applications, or the entire system, with optional visual question answering through local or remote AI models.

Code, Build and Evaluate agents - excellent Model and Skills/MCP/ACP/A2A Support

turns your codebase into an autoresearch loop — discovers what to measure, instruments the benchmark, then runs tree search with parallel subagents.

Samurai-inspired multi-agent system for Claude Code. Orchestrate parallel AI tasks via tmux with shogun → karo → ashigaru hierarchy.

lnwjud — local AI-agent runtime & MCP gateway

🐙 ADLC Team Skills — Agentic SDLC for Engineering Teams

Helping the Agents Compose the Things

🤖🤮 Hate the yuck codes that agents generated? Try `alint`, a ESLint like toolchain for intent driven code check, freeze your skills, AGENTS.md to lint rules