Codex plugin for Claude Code

Use Codex from inside Claude Code for code reviews or to delegate tasks to Codex.

This plugin is for Claude Code users who want an easy way to start using Codex from the workflow
they already have.

What You Get

• /codex:review for a normal read-only Codex review
• /codex:adversarial-review for a steerable challenge review
• /codex:rescue, /codex:transfer, /codex:status, /codex:result, and /codex:cancel to delegate work, hand off sessions, and manage background jobs

Requirements

• ChatGPT subscription (incl. Free) or OpenAI API key.
• Usage will contribute to your Codex usage limits. Learn more.
• Node.js 18.18 or later

Install

Add the marketplace in Claude Code:

/plugin marketplace add openai/codex-plugin-cc

Install the plugin:

/plugin install codex@openai-codex

Reload plugins:

/reload-plugins

Then run:

/codex:setup

/codex:setup will tell you whether Codex is ready. If Codex is missing and npm is available, it can offer to install Codex for you.

If you prefer to install Codex yourself, use:

npm install -g @openai/codex

If Codex is installed but not logged in yet, run:

!codex login

After install, you should see:

• the slash commands listed below
• the codex:codex-rescue subagent in /agents

One simple first run is:

/codex:review --background
/codex:status
/codex:result

Usage

/codex:review

Runs a normal Codex review on your current work. It gives you the same quality of code review as running /review inside Codex directly.

[!NOTE]
Code review especially for multi-file changes might take a while. It's generally recommended to run it in the background.

Use it when you want:

• a review of your current uncommitted changes
• a review of your branch compared to a base branch like main

Use --base <ref> for branch review. It also supports --wait and --background. It is not steerable and does not take custom focus text. Use /codex:adversarial-review when you want to challenge a specific decision or risk area.

Examples:

/codex:review
/codex:review --base main
/codex:review --background

This command is read-only and will not perform any changes. When run in the background you can use /codex:status to check on the progress and /codex:cancel to cancel the ongoing task.

/codex:adversarial-review

Runs a steerable review that questions the chosen implementation and design.

It can be used to pressure-test assumptions, tradeoffs, failure modes, and whether a different approach would have been safer or simpler.

It uses the same review target selection as /codex:review, including --base <ref> for branch review.
It also supports --wait and --background. Unlike /codex:review, it can take extra focus text after the flags.

Use it when you want:

• a review before shipping that challenges the direction, not just the code details
• review focused on design choices, tradeoffs, hidden assumptions, and alternative approaches
• pressure-testing around specific risk areas like auth, data loss, rollback, race conditions, or reliability

Examples:

/codex:adversarial-review
/codex:adversarial-review --base main challenge whether this was the right caching and retry design
/codex:adversarial-review --background look for race conditions and question the chosen approach

This command is read-only. It does not fix code.

/codex:rescue

Hands a task to Codex through the codex:codex-rescue subagent.

Use it when you want Codex to:

• investigate a bug
• try a fix
• continue a previous Codex task
• take a faster or cheaper pass with a smaller model

[!NOTE]
Depending on the task and the model you choose these tasks might take a long time and it's generally recommended to force the task to be in the background or move the agent to the background.

It supports --background, --wait, --resume, and --fresh. If you omit --resume and --fresh, the plugin can offer to continue the latest rescue thread for this repo.

Examples:

/codex:rescue investigate why the tests started failing
/codex:rescue fix the failing test with the smallest safe patch
/codex:rescue --resume apply the top fix from the last run
/codex:rescue --model gpt-5.4-mini --effort medium investigate the flaky integration test
/codex:rescue --model spark fix the issue quickly
/codex:rescue --background investigate the regression

You can also just ask for a task to be delegated to Codex:

Ask Codex to redesign the database connection to be more resilient.

Notes:

• if you do not pass --model or --effort, Codex chooses its own defaults.
• if you say spark, the plugin maps that to gpt-5.3-codex-spark
• follow-up rescue requests can continue the latest Codex task in the repo

/codex:transfer

Creates a persistent Codex thread from the current Claude Code session and prints a codex resume <session-id> command.

Use it when you started a debugging or implementation conversation in Claude Code and want to continue that same context directly in Codex.

Examples:

/codex:transfer
/codex:transfer --source ~/.claude/projects/-Users-me-repo/<session-id>.jsonl

The plugin's existing SessionStart hook supplies the current transcript path automatically; --source is available as a manual override. The transfer uses Codex's external-agent session importer, so it follows the same conversion rules as importing Claude history in the Codex App and creates visible turns that can be continued in the App or TUI. The source must be under ~/.claude/projects, and older Codex versions that do not expose session import must be upgraded before using this command.

/codex:status

Shows running and recent Codex jobs for the current repository.

Examples:

/codex:status
/codex:status task-abc123

Use it to:

• check progress on background work
• see the latest completed job
• confirm whether a task is still running

/codex:result

Shows the final stored Codex output for a finished job.
When available, it also includes the Codex session ID so you can reopen that run directly in Codex with codex resume <session-id>.

Examples:

/codex:result
/codex:result task-abc123

/codex:cancel

Cancels an active background Codex job.

Examples:

/codex:cancel
/codex:cancel task-abc123

/codex:setup

Checks whether Codex is installed and authenticated.
If Codex is missing and npm is available, it can offer to install Codex for you.

You can also use /codex:setup to manage the optional review gate.

Enabling review gate

/codex:setup --enable-review-gate
/codex:setup --disable-review-gate

When the review gate is enabled, the plugin uses a Stop hook to run a targeted Codex review based on Claude's response. If that review finds issues, the stop is blocked so Claude can address them first.

[!WARNING]
The review gate can create a long-running Claude/Codex loop and may drain usage limits quickly. Only enable it when you plan to actively monitor the session.

Typical Flows

Review Before Shipping

/codex:review

Hand A Problem To Codex

/codex:rescue investigate why the build is failing in CI

Start Something Long-Running

/codex:adversarial-review --background
/codex:rescue --background investigate the flaky test

Then check in with:

/codex:status
/codex:result

Codex Integration

The Codex plugin wraps the Codex app server. It uses the global codex binary installed in your environment and [applies the same configuration](https://developers.openai.c

(Preview — first 8 000 chars. View full README ↗)

why use many token when few do trick

Make your AI coding agent talk like a caveman.
Same answers, 65% fewer output tokens. Brain still big. Mouth small.

See it · Install · Levels · What you get · Benchmarks · Ecosystem · Caveman 2

Caveman is a skill/plugin for Claude Code, Codex, Gemini, Cursor, Windsurf, Cline, Copilot, and 30+ other agents. Install once. Agent drops the filler and answers in tight caveman-speak, keeping code, commands, and errors byte-for-byte exact. You save output tokens on every reply, forever.

Before / After

🗣️ Normal agent — 69 tokens	Caveman agent — 19 tokens
> The reason your React component is re-rendering is likely because you're creating a new object reference on each render cycle. When you pass an inline object as a prop, React's shallow comparison sees it as a different object every time, which triggers a re-render. I'd recommend using useMemo to memoize the object.	> New object ref each render. Inline object prop = new ref = re-render. Wrap in `useMemo`.
> Sure! I'd be happy to help you with that. The issue you're experiencing is most likely caused by your authentication middleware not properly validating the token expiry. Let me take a look and suggest a fix.	> Bug in auth middleware. Token expiry check use `<` not `<=`. Fix:

Same fix. Third of the words. Nothing technical lost.

┌────────────────────────────────────────────┐
│   output tokens saved   █████████       65% │
│   input tokens saved    ░░░░░░░░░         0% │
│   technical accuracy    █████████      100% │
│   vibes                 █████████       OOG │
└────────────────────────────────────────────┘

Caveman no make brain smaller. Caveman make mouth smaller. Shrinks what the agent says, not what it knows.

Install

One command. Finds every agent on your machine. Installs for each.

# macOS · Linux · WSL · Git Bash
curl -fsSL https://raw.githubusercontent.com/JuliusBrussee/caveman/main/install.sh | bash

# Windows · PowerShell 5.1+
irm https://raw.githubusercontent.com/JuliusBrussee/caveman/main/install.ps1 | iex

~30 seconds. Needs Node ≥18. Skips agents you no have. Safe to re-run.

[!TIP]
Turn it on: type /caveman or say "talk like caveman". Turn it off: say "normal mode". On Claude Code, Codex, and Gemini it's already on from message one. No command needed.

# Claude Code plugin
claude plugin marketplace add JuliusBrussee/caveman && claude plugin install caveman@caveman

# Gemini CLI extension
gemini extensions install https://github.com/JuliusBrussee/caveman

# Cursor / Windsurf / Cline / Codex / 30+ more, via the skills registry
npx skills add JuliusBrussee/caveman -a cursor

Pick your grunt

Six levels. Switch anytime with /caveman <level>. Level sticks until you change it or the session ends.

[!NOTE]
Speak your tongue. Caveman keeps your language. Write Portuguese, caveman grunt Portuguese. Spanish, French, same. It compresses the style, never translates. wenyan mode is the exception on purpose: classical Chinese packs the most meaning per token.

What you get

[!TIP]
On Claude Code the statusline shows [CAVEMAN] ⛏ 12.4k — that's your lifetime tokens saved, updated on every /caveman-stats. Silence it with CAVEMAN_STATUSLINE_SAVINGS=0.

Benchmarks

Real token counts from the Claude API. Average 65% output reduction across 10 prompts (range 22–87%), measured against default verbose replies. Output tokens only, committed and reproducible in benchmarks/ and evals/.

[!IMPORTANT]
Honest number warning. Caveman only shrinks output tokens. Input and reasoning tokens are untouched, and the skill itself adds ~1–1.5k input tokens per turn. So whole-session savings run smaller than the output number, and on already-terse workloads they can go net-negative. The real win is readability and speed. Cost savings are the bonus. When caveman wins, when it loses, and how to measure it yourself: docs/HONEST-NUMBERS.md.

Turns out short isn't just cheaper

(Preview — first 8 000 chars. View full README ↗)

Page Agent

The GUI Agent Living in Your Webpage. Control web interfaces with natural language.

🌐 English | 中文

🚀 Demo | 📖 Docs | 📢 HN Discussion | 𝕏 Follow on X

https://github.com/user-attachments/assets/a1f2eae2-13fb-4aae-98cf-a3fc1620a6c2

✨ Features

• 🎯 Easy integration
  • No need for browser extension / python / headless browser.
  • Just in-page javascript. Everything happens in your web page.
• 📖 Text-based DOM manipulation
  • No screenshots. No multi-modal LLMs or special permissions needed.
• 🧠 Bring your own LLMs
• 🐙 Optional chrome extension for multi-page tasks.
  • And an MCP Server (Beta) to control it from outside

💡 Use Cases

• SaaS AI Copilot — Ship an AI copilot in your product in lines of code. No backend rewrite.
• Smart Form Filling — Turn 20-click workflows into one sentence. Perfect for ERP, CRM, and admin systems.
• Accessibility — Make any web app accessible through natural language. Voice commands, screen readers, zero barrier.
• Multi-page Agent — Extend your own web agent's reach across browser tabs chrome extension.
• MCP - Allow your agent clients to control your browser.

🚀 Quick Start

One-line integration

Fastest way to try PageAgent with our free Demo LLM:

<script src="{URL}" crossorigin="true"></script>

⚠️ For technical evaluation only. This demo CDN uses our free testing LLM API. By using it, you agree to its terms.

Add ?autoInit=false to load the script without creating the demo agent automatically. You can then instantiate it with new window.PageAgent(...).

NPM Installation

npm install page-agent

import { PageAgent } from 'page-agent'

const agent = new PageAgent({
    model: 'qwen3.5-plus',
    baseURL: 'https://dashscope.aliyuncs.com/compatible-mode/v1',
    apiKey: 'YOUR_API_KEY',
    language: 'en-US',
})

await agent.execute('Click the login button')

For more programmatic usage, see 📖 Documentations.

🌟 Awesome Page Agent

Built something cool with PageAgent? Add it here! Open a PR to share your project.

These are community projects — not maintained or endorsed by us. Use at your own discretion.

🤝 Contributing

We welcome contributions from the community! See CONTRIBUTING.md for guidelines and docs/developer-guide.md for local development workflows.

Please read the maintainer's note on principles and current state.

Contributions generated entirely by bots or AI without substantial human involvement will not be accepted.

⚖️ License

MIT License

👏 Acknowledgments

This project builds upon the excellent work of browser-use.

PageAgent is designed for client-side web enhancement, not server-side automation.

DOM processing components and prompt are derived from browser-use:

Browser Use <https://github.com/browser-use/browser-use>
Copyright (c) 2024 Gregor Zunic
Licensed under the MIT License

We gratefully acknowledge the browser-use project and its contributors for their
excellent work on web automation and DOM interaction patterns that helped make
this project possible.

⭐ Star this repo if you find PageAgent helpful!

(Preview — first 8 000 chars. View full README ↗)

# Strix ### The open-source AI pentesting tool. Autonomous AI hackers that find and fix your app’s vulnerabilities.
[](https://discord.gg/strix-ai)

[!TIP]
New! Strix integrates seamlessly with GitHub Actions and CI/CD pipelines. Automatically scan for vulnerabilities on every pull request and block insecure code before it reaches production - Get started with no setup required.

Strix Overview

Strix are autonomous AI penetration testing agents that act just like real hackers - they run your code dynamically, find vulnerabilities, and validate them through actual proofs-of-concept. Built for developers and security teams who need fast, accurate security testing without the overhead of manual pentesting or the false positives of static analysis tools.

Key Capabilities:

• Full pentesting toolkit - reconnaissance, exploitation, and validation out of the box
• Multi-agent orchestration - teams of AI pentesters that collaborate and scale
• Real exploit validation - working PoCs, not false positives like legacy vulnerability scanners
• Developer‑first CLI - actionable findings with remediation guidance
• Auto‑fix & reporting - generate patches and compliance-ready pentest reports

Use Cases

• Application Security Testing - Detect and validate critical vulnerabilities in your applications
• Rapid Penetration Testing - Get penetration tests done in hours, not weeks, with compliance reports
• Bug Bounty Automation - Automate bug bounty research and generate PoCs for faster reporting
• CI/CD Integration - Run tests in CI/CD to block vulnerabilities before reaching production

🚀 Quick Start

Prerequisites:
- Docker (running)
- An LLM API key from any supported provider (OpenAI, Anthropic, Google, etc.)

Installation & First Scan

# Install Strix
curl -sSL https://strix.ai/install | bash

# Configure your AI provider
export STRIX_LLM="openai/gpt-5.4"
export LLM_API_KEY="your-api-key"

# Run your first security assessment
strix --target ./app-directory

[!NOTE]
First run automatically pulls the sandbox Docker image. Results are saved to strix_runs/<run-name>

☁️ Strix Platform

Try the Strix full-stack penetration testing platform at app.strix.ai - sign up for free, connect your repos and domains, and launch a pentest in minutes.

• Validated findings with PoCs - every vulnerability includes a working proof-of-concept exploit and reproduction steps
• One-click autofix - AI-generated security patches as ready-to-merge pull requests
• Continuous pentesting - always-on vulnerability scanning that keeps pace with your deployments
• DevSecOps integrations - GitHub, GitLab, Bitbucket, Slack, Jira, Linear, and CI/CD pipelines
• Continuous learning - AI that builds on past findings, adapts to your codebase, and reduces false positives over time

Start your first pentest →

✨ Features

Agentic Pentesting Tools

Strix agents come equipped with a comprehensive offensive security toolkit - the same tools used by professional penetration testers and ethical hackers:

• HTTP Interception Proxy - Full request/response manipulation and analysis with Caido
• Browser Exploitation - Automated browser for testing XSS, CSRF, clickjacking, and auth bypass flows
• Shell & Command Execution - Interactive terminal for exploit development and post-exploitation
• Custom Exploit Runtime - Python sandbox for writing and validating proof-of-concept exploits
• Reconnaissance & OSINT - Automated attack surface mapping, subdomain enumeration, and fingerprinting
• Static & Dynamic Code Analysis - SAST + DAST capabilities for comprehensive application security testing
• Vulnerability Knowledge Base - Structured findings with CVSS scoring and OWASP classification

Comprehensive Vulnerability Scanner

Strix identifies, validates, and exploits a wide range of security vulnerabilities across the OWASP Top 10 and beyond:

• Broken Access Control - IDOR, privilege escalation, auth bypass
• Injection Attacks - SQL injection, NoSQL injection, OS command injection, SSTI
• Server-Side Vulnerabilities - SSRF, XXE, insecure deserialization, RCE
• Client-Side Attacks - XSS (stored/reflected/DOM), prototype pollution, CSRF
• Business Logic Flaws - Race conditions, payment manipulation, workflow bypass
• Authentication & Session - JWT attacks, session fixation, credential stuffing vectors
• Infrastructure & Cloud - Misconfigurations, exposed services, cloud security issues
• API Security - Broken authentication, mass assignment, rate limiting bypass

Graph of Agents (Multi-Agent Pentesting)

Advanced multi-agent orchestration for comprehensive automated penetration testing:

• Distributed Pentesting - Specialized AI agents for recon, exploitation, and post-exploitation
• Scalable Security Testing - Parallel execution across multiple targets for fast, comprehensive coverage
• Dynamic Coordination - Agents share discoveries, chain vulnerabilities, and collaborate like a red team

Usage Examples

Basic Usage

# Scan a local codebase
strix --target ./app-directory

# Security review of a GitHub repository
strix --target https://github.com/org/repo

# Black-box web application assessment
strix --target https://your-app.com

Advanced Testing Scenarios

```bash

Grey-box authenticated testing

strix --target https://your-app.com --instruction "Perform authenticated testing using credentials: user:pass"

Multi-target testing (source code + deployed app)

strix -t https://github.com/org/app -t https://your-app.com

White-box source-aware scan (local repository)

strix --target ./app-directory --scan-mode standard

Focused testing with custom instructions

strix --target api.your-app.com --instruction "Focus on business logic flaws and IDOR vulnerabilities"

Provide detailed instructions through file (e.g., rules of engagement, scope, exclusions)

strix --target api.your-app.com --instruction-file ./instruction.md

Force PR diff-scope

(Preview — first 8 000 chars. View full README ↗)

Chrome DevTools for agents

Chrome DevTools for agents (chrome-devtools-mcp) lets your coding agent (such as Antigravity, Claude, Cursor or Copilot)
control and inspect a live Chrome browser. It acts as a Model-Context-Protocol
(MCP) server, giving your AI coding assistant access to the full power of
Chrome DevTools for reliable automation, in-depth debugging, and performance analysis.
A CLI is also provided for use without MCP.

Tool reference | Changelog | Contributing | Troubleshooting | Design Principles

Key features

• Get performance insights: Uses Chrome
  DevTools to record
  traces and extract actionable performance insights.
• Advanced browser debugging: Analyze network requests, take screenshots and
  check browser console messages (with source-mapped stack traces).
• Reliable automation. Uses
  puppeteer to automate actions in
  Chrome and automatically wait for action results.

Disclaimers

chrome-devtools-mcp exposes content of the browser instance to the MCP clients
allowing them to inspect, debug, and modify any data in the browser or DevTools.
Avoid sharing sensitive or personal information that you don't want to share with
MCP clients.

chrome-devtools-mcp officially supports Google Chrome and Chrome for Testing only.
Other Chromium-based browsers may work, but this is not guaranteed, and you may encounter unexpected behavior. Use at your own discretion.
We are committed to providing fixes and support for the latest version of Extended Stable Chrome.

Performance tools may send trace URLs to the Google CrUX API to fetch real-user
experience data. This helps provide a holistic performance picture by
presenting field data alongside lab data. This data is collected by the Chrome
User Experience Report (CrUX). To disable
this, run with the --no-performance-crux flag.

Usage statistics

Google collects usage statistics (such as tool invocation success rates, latency, and environment information) to improve the reliability and performance of Chrome DevTools MCP.

Data collection is enabled by default. You can opt-out by passing the --no-usage-statistics flag when starting the server:

"args": ["-y", "chrome-devtools-mcp@latest", "--no-usage-statistics"]

Google handles this data in accordance with the Google Privacy Policy.

Google's collection of usage statistics for Chrome DevTools MCP is independent from the Chrome browser's usage statistics. Opting out of Chrome metrics does not automatically opt you out of this tool, and vice-versa.

Collection is disabled if CHROME_DEVTOOLS_MCP_NO_USAGE_STATISTICS or CI env variables are set.

Update checks

By default, the server periodically checks the npm registry for updates and logs a notification when a newer version is available.
You can disable these update checks by setting the CHROME_DEVTOOLS_MCP_NO_UPDATE_CHECKS environment variable.

Requirements

• Node.js LTS version.
• Chrome current stable version or newer.
• npm

Getting started

Add the following config to your MCP client:

{
  "mcpServers": {
    "chrome-devtools": {
      "command": "npx",
      "args": ["-y", "chrome-devtools-mcp@latest"]
    }
  }
}

[!NOTE]
Using chrome-devtools-mcp@latest ensures that your MCP client will always use the latest version of the Chrome DevTools MCP server.

If you are interested in doing only basic browser tasks, use the --slim mode:

{
  "mcpServers": {
    "chrome-devtools": {
      "command": "npx",
      "args": ["-y", "chrome-devtools-mcp@latest", "--slim", "--headless"]
    }
  }
}

See Slim tool reference.

MCP Client configuration

amp mcp add chrome-devtools -- npx chrome-devtools-mcp@latest

{
  "mcpServers": {
    "chrome-devtools": {
      "command": "npx",
      "args": [
        "-y",
        "chrome-devtools-mcp@latest",
        "--browser-url=http://127.0.0.1:9222"
      ]
    }
  }
}

claude mcp add chrome-devtools --scope user npx chrome-devtools-mcp@latest

/plugin marketplace add ChromeDevTools/chrome-devtools-mcp

/plugin install chrome-devtools-mcp@chrome-devtools-plugins

codex mcp add chrome-devtools -- npx chrome-devtools-mcp@latest

[mcp_servers.chrome-devtools]
command = "cmd"
args = [
    "/c",
    "npx",
    "-y",
    "chrome-devtools-mcp@latest",
]
env = { SystemRoot="C:\\Windows", PROGRAMFILES="C:\\Program Files" }
startup_timeout_ms = 20_000

cmd mcp add chrome-devtools --scope user npx chrome-devtools-mcp@latest

(Preview — first 8 000 chars. View full README ↗)

Privacy-First AI Meeting Assistant

Open Source • Privacy-First • Enterprise-Ready

Get latest Product updates

Website • LinkedIn • Meetily Discord • Privacy-First AI • Reddit

A privacy-first AI meeting assistant that captures, transcribes, and summarizes meetings entirely on your infrastructure. Built by expert AI engineers passionate about data sovereignty and open source solutions. Perfect for enterprises that need advanced meeting intelligence without compromising on privacy, compliance, or control.

View full Demo Video

Meetily PRO Upgrade Offer - Meetily PRO is available for users who need enhanced accuracy, advanced exports, custom summary workflows, and team-ready features. Use coupon code LAUNCH20 for 20% off until the next Meetily Community Edition release. Speaker diarization is also planned for PRO in mid-June. Explore Meetily PRO →

Introduction

Meetily is a privacy-first AI meeting assistant that runs entirely on your local machine. It captures your meetings, transcribes them in real-time, and generates summaries, all without sending any data to the cloud. This makes it the perfect solution for professionals and enterprises who need to maintain complete control over their sensitive information.

Why Meetily?

While there are many meeting transcription tools available, this solution stands out by offering:

• Privacy First: All processing happens locally on your device.
• Cost-Effective: Uses open-source AI models instead of expensive APIs.
• Flexible: Works offline and supports multiple meeting platforms.
• Customizable: Self-host and modify for your specific needs.

Features

• Local First: All processing is done on your machine. No data ever leaves your computer.
• Real-time Transcription: Get a live transcript of your meeting as it happens.
• AI-Powered Summaries: Generate summaries of your meetings using powerful language models.
• Multi-Platform: Works on macOS, Windows, and Linux.
• Open Source: Meetily is open source and free to use.
• Flexible AI Provider Support: Choose from Ollama (local), Claude, Groq, OpenRouter, or use your own OpenAI-compatible endpoint.

Installation

🪟 Windows

1. Download the latest x64-setup.exe from Releases
2. Run the installer

🍎 macOS

1. Download meetily_0.4.0_aarch64.dmg from Releases
2. Open the downloaded .dmg file
3. Drag Meetily to your Applications folder
4. Open Meetily from Applications folder

🐧 Linux

Build from source following our detailed guides:

• Building on Linux
• General Build Instructions

Quick start:

git clone https://github.com/Zackriya-Solutions/meeting-minutes
cd meeting-minutes/frontend
pnpm install
./build-gpu.sh

Key Features in Action

🎯 Local Transcription

Transcribe meetings entirely on your device using Whisper or Parakeet models. No cloud required.

📥 Import & Enhance Beta

Import existing audio files to generate transcripts, or enhance to re-transcribe any recorded meeting with a different model or language, all processed locally.

Contributed by Jeremi Joslin, improved by Vishnu P S and Mohammed Safvan

🤖 AI-Powered Summaries

Generate meeting summaries with your choice of AI provider. Ollama (local) is recommended, with support for Claude, Groq, OpenRouter, and OpenAI.

🔒 Privacy-First Design

All data stays on your machine. Transcription models, recordings, and transcripts are stored locally.

🌐 Custom OpenAI Endpoint Support

Use your own OpenAI-compatible endpoint for AI summaries. Perfect for organizations with custom AI i

(Preview — first 8 000 chars. View full README ↗)

As seen in The Washington Post: See the hidden rules behind AI. Then use them to rewrite this article. (May 11, 2026)

System Prompts Leaks

The purpose of this repo is to document the System Prompt instructions for all the AI chatbots out there - Claude, ChatGPT, Gemini etc.

🆕 Diff: Claude Opus 4.8 → Claude Fable 5 — see exactly what changed in the claude.ai system prompt for Anthropic's newest model

Recently Updated

Anthropic — Claude

OpenAI — ChatGPT

(Preview — first 8 000 chars. View full README ↗)

Machine Learning Systems

Principles and Practices of Engineering Artificially Intelligent Systems

English • 中文 • 日本語 • 한국어

Mission

That gap is what we mean by AI engineering.

AI engineering is the discipline of building efficient, reliable, safe, and robust intelligent systems that operate in the real world, not just models in isolation. Our mission is to establish AI engineering as a foundational discipline alongside software engineering and computer engineering, by teaching how to design, build, and evaluate end-to-end intelligent systems.

Our goal: Help 100,000 learners master ML Systems this year, and reach 1 million by 2030.

Why One Repository

I designed this as a single integrated curriculum, not a collection of independent projects. The textbook teaches the theory. TinyTorch makes you build the internals. The hardware kits force you to confront real constraints. The simulator lets you reason about infrastructure you can't afford to rent. Each piece exists because I found that students who only read don't internalize, and students who only code don't generalize.

A growing community of contributors helps improve every part of it: fixing errors, sharpening explanations, testing on new hardware. Their work makes this better for everyone, and I'm grateful for every pull request.

The Curriculum

Every component connects. The textbook gives you the mental models. The labs let you reason through trade-offs interactively, powered by MLSys·im — a modeling engine for infrastructure you can't physically access, and a standalone tool in its own right. TinyTorch makes you build the machinery yourself. The hardware kits put you face-to-face with real deployment constraints. StaffML tests whether you actually understand it. Socratiq adds AI-guided reading, contextual quizzes, and spaced repetition inside the learning experience. And the instructor hub, slides, and newsletter give educators everything they need to bring this into a classroom.

For Students

	Component	Role in the Curriculum	Link
📖	Textbook	Two-volume MIT Press textbook. The theory, the mental models, and the quantitative reasoning that everything else builds on.	Vol I · Vol II
🔬	Labs	Interactive Marimo notebooks where you explore trade-offs from the textbook: change a parameter, see what breaks, build intuition. Powered by MLSys·im under the hood.	Launch labs · Repo guide
🔥	Tiny🔥Torch	Build your own ML framework from scratch across 20 progressive modules. You don't understand a system until you've built one.	Get started
🛠️	Hardware Kits	Deploy ML to Arduino, Seeed, Grove, and Raspberry Pi devices. Real memory limits, real powe (Preview — first 8 000 chars. View full README ↗) #9 rommapp / romm A beautiful, powerful, self-hosted rom manager and player. Python ⭐ 9,954 🍴 482 ⭐ 239 stars today 📖 README A beautiful, powerful, self-hosted ROM manager and player. [![discord-badge-img]][discord-badge] [![docs-badge-img]][docs] [![license-badge-img]][license-badge] [![release-badge-img]][release-badge] [![docker-pulls-badge-img]][docker-pulls-badge] Overview RomM (ROM Manager) allows you to scan, enrich, browse and play your game collection with a clean and responsive interface. With support for multiple platforms, various naming schemes, and custom tags, RomM is a must-have for anyone who plays on emulators. Features Scan and enhance your game library with metadata from IGDB, Screenscraper and MobyGames Fetch custom artwork from [SteamGridDB][steamgriddb-api] Display your achievements from [Retroachievements][retroachievements-api] Metadata available for 400+ platforms Play games directly from the browser using EmulatorJS and RuffleRS Share your library with friends with limited access and permissions Official apps for [Playnite][playnite-app], [Android][argosy-launcher] and [CFWs][grout] Supports multi-disk games, DLCs, mods, hacks, patches, and manuals Parse and filter by tags in filenames View, upload, update, and delete games from any modern web browser Preview 🖥 Desktop 📱 Mobile Installation To start using RomM, check out the Quick Start Guide in the docs. If you are having issues with RomM, please review the page for troubleshooting steps. Contributing To contribute to RomM, please check Contribution Guide. Community Here are a few projects maintained by members of our community. Please note that the RomM team does not regularly review their source code. Mobile 🔷 [Argosy][argosy-launcher]: Native client for installing and launching games by @tmgast [romm-ios-app][romm-ios-app]: Native iOS app by @ilyas-hallak [romm-mobile][romm-mobile]: Android (and soon iOS) app by @mattsays Desktop 🔷 [Playnite plugin][playnite-app]: Library plugin for Playnite by @gantoine [RommBrowser][romm-browser]: Electron client by @smurflabs [RetroArch Sync][romm-retroarch-sync]: Sync RetroArch library with RomM by @Covin90 [RomMate][rommate]: Desktop app for browsing your collection by @brenoprata10 [romm-client][romm-client]: Desktop client by @chaun14 Handhelds 🔷 [Grout][grout]: Download client for muOS and NextUI by @BrandonKowalski [DeckRommSync][deck-romm-sync]: SteamOS downloader and syncer by @PeriBluGaming [SwitchRomM][switch-romm]: Homebrew NRO for Switch by @Shalasere Other [romm-comm][romm-comm-discord-bot]: Discord bot by @idio-sync [GGRequestz][ggrequestz]: Game discovery and request tool by @XTREEMMAK [Syncthing sync][syncthing-sync]: Small tool to push a Syncthing library to RomM by @amn-96 [🔷] Official first-party app Join us on Discord, where you can ask questions, submit ideas, get help, showcase your collection, and discuss RomM with other users. Technical Support If you have any issues with RomM, please open an issue in this repository. Financial Support Consider supporting the development of this project on Open Collective. All funds will be used to cover the costs of hosting, development, and maintenance of RomM. Our Friends Here are a few projects that we think you might like: EmulatorJS: An embeddable, browser-based emulator RetroDECK: Retro gaming on SteamOS and Linux ES-DE Frontend: Emulator frontend for Linux, macOS and Windows Gaseous: Another ROM manager with web-based emulator Retrom: A centralized game library/collection management service Drop: Steam-like experience for DRM-free games LanCommander: Digital game platform for PC games Steam ROM Manager: An app for managing ROMs in Steam     (Preview — first 8 000 chars. View full README ↗) #10 ogulcancelik / herdr agent multiplexer that lives in your terminal. Rust ⭐ 11,069 🍴 649 ⭐ 478 stars today 📖 README herdr herdr.dev · install · quick start · supported agents · docs · socket api · sponsor https://github.com/user-attachments/assets/043ec09f-4bdd-41d5-aee0-8fda6b83e267 run all your coding agents in one terminal. see who's blocked, working, or done at a glance. run your agents where they already run; your machine, a server, anywhere you can ssh. each one gets its own real terminal, not an app's imitation of one, so even full-screen TUIs render right. click, drag, and split panes into workspaces and tabs, and watch each agent go blocked, working, done. close the laptop and nothing dies; reattach from another terminal, or from your phone over ssh. one local rust binary, not an app: no gui, no electron, no mac-only wrapper, no account, no telemetry. (if you've used tmux: it's that, rebuilt for agents.) what you get a real terminal per agent. you see each agent's own screen, not an app's imitation of one, so even full-screen TUIs render right. agent state at a glance. the sidebar rolls every agent up to 🔴 blocked, 🟡 working, 🔵 done, or 🟢 idle, so you always know who needs you. zero config, no hooks required. workspaces, tabs, panes. organize by repo or folder, click, drag, and split, mouse-native throughout. nothing dies on detach. a background server keeps panes and agents alive; detach and reattach from any terminal, including your phone over ssh. runs anywhere. single ~10MB rust binary, linux and macos (windows beta), no dependencies, runs inside the terminal you already use. scriptable. a local socket api and cli that agents can drive, plus plugins you can write in any language. how it compares tmux gui managers herdr persistent sessions ✓ — ✓ detach / reattach ✓ — ✓ runs anywhere, over ssh ✓ — ✓ panes, tabs, workspaces ✓ ✓ ✓ agent awareness — ✓ ✓ lives in your terminal ✓ — ✓ real terminal views ✓ — ✓ mouse-native — ✓ ✓ lightweight binary ✓ — ✓ agents can orchestrate ? ? ✓ tmux gives you persistence and panes, but it was built before agents existed. it has no idea which pane is blocked, working, or done; you can bolt a bell character and per-harness hooks onto it, but you wire each one yourself and still have no shared view of the fleet. the gui agent managers (conductor, cmux, emdash) do show agent state, so call that table stakes. the difference is everything around it. they are apps, often mac-only and closed, that redraw the terminal inside a wrapper. herdr is a single binary that runs in the terminal you already use, anywhere you can ssh, and shows each agent's real screen on a server that keeps it alive when you disconnect. see the full comparison with tmux, zellij, cmux, warp, conductor, and more. install curl -fsSL https://herdr.dev/install.sh | sh windows preview beta: powershell -ExecutionPolicy Bypass -c "irm https://herdr.dev/install.ps1 | iex" also available with brew install herdr, mise use -g herdr, nix run github:ogulcancelik/herdr, or as a stable Linux/macOS binary from releases. herdr update upgrades an installer-managed install; Homebrew, mise, and Nix update through their own package managers. channel, preview, restart, and restore details are in the install docs. quick start herdr herdr starts or attaches to a background server and opens a workspace. run an agent in the pane. herdr is mouse-native, so clicking and dragging panes, tabs, and split borders gets you everywhere without a single keybinding. for the keyboard, ctrl+b is the prefix: press it, release, then press the action key, so ctrl+b then c makes a tab. one reserved key keeps herdr out of your shell's way. ctrl+b then shift+n for a new workspace ctrl+b then v or minus to split panes ctrl+b then c for a new tab ctrl+b then w to switch workspaces ctrl+b then q to detach; agents keep running, run herdr again to reattach press ctrl+b then ? for every binding. the keyboard guide explains the prefix model and how to go prefix-free; the full keymap, copy mode, and config syntax live in the configuration docs. remote run herdr on a VPS and reach it from your local terminal. herdr --remote makes your local terminal the client of the remote server, so pasting images into your agents keeps working, the thing plain ssh + tmux breaks. herdr --remote workbox herdr --remote ssh://you@yourserver:2222 see the persistence and remote docs for named sessions, keepalives, direct attach, and handoff. supported agents detection works out of the box with process-name matching plus terminal-output heuristics. agent idle / done working blocked pi ✓ ✓ partial claude code ✓ ✓ ✓ codex ✓ ✓ ✓ droid ✓ ✓ ✓ amp ✓ ✓ ✓ opencode ✓ ✓ ✓ grok cli ✓ ✓ ✓ hermes agent ✓ ✓ ✓ kilo code cli ✓ ✓ ✓ devin cli ✓ ✓ ✓ cursor agent ✓ ✓ ✓ antigravity cli ✓ ✓ ✓ kimi code cli ✓ ✓ ✓ github copilot cli ✓ ✓ ✓ qodercli ✓ ✓ ✓ kiro cli ✓ ✓ — detected but not fully tested: gemini cli, cline. any other agent still works; herdr runs it as a terminal multiplexer, and custom integrations can report labels and state over the socket api. official integrations add native session restore, and some report semantic state directly. install one with herdr integration install <agent>, available for pi, omp, claude, codex, copilot, devin, droid, kimi, opencode, kilo, hermes, qodercli, and cursor. see the integrations docs. agents can use herdr too the local Unix socket lets agents create workspaces, split or zoom panes, spawn helpers, read output, and subscribe to state changes instead of polling. install the reusable skill with: npx skills add ogulcancelik/herdr --skill herdr -g start with the agent skill docs, socket API docs, and SKILL.md. docs quick start: first session, panes, copy, and named sessions concepts: server and client (Preview — first 8 000 chars. View full README ↗) #11 dotnet / skills Repository for skills to assist AI coding agents with .NET and C# C# ⭐ 3,666 🍴 278 ⭐ 33 stars today 📖 README .NET Agent Skills This repository contains the .NET team's curated set of core skills and custom agents for coding agents. For information about the Agent Skills standard, see agentskills.io. 📊 Dashboard - Accuracy and efficiency scoring trends for contained plugins (https://dotnet.github.io/skills/) What's Included Plugin Description dotnet C# language server (LSP) integration for coding agents and high-level .NET development skills. dotnet-advanced Collection of .NET skills for handling specific .NET tasks for special scenarios. dotnet-data Skills for .NET data access and Entity Framework related tasks. dotnet-diag Skills for .NET performance investigations, debugging, and incident analysis. dotnet-msbuild Comprehensive MSBuild and .NET build skills: failure diagnosis, performance optimization, code quality, and modernization. dotnet-nuget NuGet and .NET package management: dependency management and modernization. dotnet-upgrade Skills for migrating and upgrading .NET projects across framework versions, language features, and compatibility targets. dotnet-maui Skills for .NET MAUI development: environment setup, diagnostics, and troubleshooting. dotnet-ai AI and ML skills for .NET: technology selection, LLM integration, agentic workflows, RAG pipelines, MCP, and classic ML with ML.NET. dotnet-template-engine .NET Template Engine skills: template discovery, project scaffolding, and template authoring. dotnet-test Skills for running, generating, analyzing, and improving .NET tests: test execution, filtering, platform detection, coverage, testability, and MSTest workflows. dotnet-test-migration Skills and an orchestrator agent for migrating .NET test frameworks and platforms: MSTest and xUnit version upgrades, xUnit-to-MSTest conversion, and VSTest to Microsoft.Testing.Platform. dotnet-aspnetcore ASP.NET Core web development skills including middleware, endpoints, real-time communication, and API patterns. dotnet-blazor Skills for Blazor development: component authoring, interactivity, and web application patterns. dotnet11 Skills for new .NET 11 APIs and language features. Installation 🚀 Plugins - Copilot CLI / Claude Code Launch Copilot CLI or Claude Code Add the marketplace: /plugin marketplace add dotnet/skills Install a plugin: /plugin install <plugin>@dotnet-agent-skills Restart to load the new plugins View available skills: /skills View available agents: /agents Update plugin (on demand): /plugin update <plugin>@dotnet-agent-skills VS Code / VS Code Insiders (Preview) [!IMPORTANT] VS Code plugin support is a preview feature and subject to change. You may need to enable it first. // settings.json { "chat.plugins.enabled": true, "chat.plugins.marketplaces": ["dotnet/skills"] } Once configured, type /plugins in Copilot Chat or use the @agentPlugins filter in Extensions to browse and install plugins from the marketplace. Cursor This repository is a Cursor plugin marketplace. You can discover and install published plugins directly in Cursor: Open the marketplace panel in Cursor Search for .NET or browse cursor.com/marketplace Install the desired plugins For local development or unpublished changes, import plugins from a local checkout: Copy or symlink your local checkout to ~/.cursor/plugins/local/dotnet-agent-skills Restart Cursor or run Developer: Reload Window Codex CLI Skills in this repository follow the agentskills.io open standard and are compatible with OpenAI Codex. Plugin marketplace (recommended) Codex CLI v0.121.0 and later supports a plugin marketplace. This repository ships a Codex-native marketplace manifest at .agents/plugins/marketplace.json, so you can register dotnet/skills as a marketplace and install plugins from it directly. Add the marketplace: bash codex plugin marketplace add dotnet/skills Launch Codex and open the plugin browser: /plugins Browse the dotnet-agent-skills tab and install the desired plugins. Update plugins on demand: bash codex plugin marketplace upgrade dotnet-agent-skills Individual skills You can also install individual skills using the skill-installer CLI with the GitHub URL: $ skill-installer install https://github.com/dotnet/skills/tree/main/plugins/<plugin>/skills/<skill-name> Contributing See CONTRIBUTING.md for contribution guidelines and how to add a new plugin. License See LICENSE for details. (Preview — first 8 000 chars. View full README ↗) #12 agentskills / agentskills Specification and documentation for Agent Skills Python ⭐ 22,157 🍴 1,402 ⭐ 406 stars today 📖 README Agent Skills A standardized way to give AI agents new capabilities and expertise. What are Agent Skills? Agent Skills are a lightweight, open format for extending AI agent capabilities with specialized knowledge and workflows. At its core, a skill is a folder containing a SKILL.md file. This file includes metadata (name and description, at minimum) and instructions that tell an agent how to perform a specific task. Skills can also bundle scripts, reference materials, templates, and other resources. my-skill/ ├── SKILL.md # Required: metadata + instructions ├── scripts/ # Optional: executable code ├── references/ # Optional: documentation ├── assets/ # Optional: templates, resources └── ... # Any additional files or directories Why Agent Skills? Agents are increasingly capable, but often don't have the context they need to do real work reliably. Skills solve this by packaging procedural knowledge and company-, team-, and user-specific context into portable, version-controlled folders that agents load on demand. This gives agents: Domain expertise: Capture specialized knowledge — from legal review processes to data analysis pipelines to presentation formatting — as reusable instructions and resources. Repeatable workflows: Turn multi-step tasks into consistent, auditable procedures. Cross-product reuse: Build a skill once and use it across any skills-compatible agent. How do Agent Skills work? Agents load skills through progressive disclosure, in three stages: Discovery: At startup, agents load only the name and description of each available skill, just enough to know when it might be relevant. Activation: When a task matches a skill's description, the agent reads the full SKILL.md instructions into context. Execution: The agent follows the instructions, optionally executing bundled code or loading referenced files as needed. Full instructions load only when a task calls for them, so agents can keep many skills on hand with only a small context footprint. Where can I use Agent Skills? Agent Skills are supported by a large number of AI tools and agentic clients — see the Client Showcase to explore some of them! Getting started Documentation — Guides and tutorials Specification — Format details Example Skills — See what's possible Discord — Share what you're building! Open development The Agent Skills format was originally developed by Anthropic, released as an open standard, and has been adopted by a growing number of agent products. The standard is open to contributions from the broader ecosystem — see CONTRIBUTING.md for how to get involved. License Code in this repository is licensed under Apache 2.0. Documentation is licensed under CC-BY-4.0. See individual directories for details. (Preview — first 8 000 chars. View full README ↗) #13 immich-app / immich High performance self-hosted photo and video management solution. TypeScript ⭐ 105,369 🍴 6,015 ⭐ 308 stars today 📖 README High performance self-hosted photo and video management solution Català Español Français Italiano 日本語 한국어 Deutsch Nederlands Türkçe 简体中文 正體中文 Українська Русский Português Brasileiro Svenska العربية Tiếng Việt ภาษาไทย [!WARNING] ⚠️ Always follow 3-2-1 backup plan for your precious photos and videos! [!NOTE] You can find the main documentation, including installation guides, at https://immich.app/. Links Documentation About Installation Roadmap Demo Features Translations Contributing Demo Access the demo here. For the mobile app, you can use https://demo.immich.app for the Server Endpoint URL. Login credentials Email Password demo@immich.app demo Features Features Mobile Web Upload and view videos and photos Yes Yes Auto backup when the app is opened Yes N/A Prevent duplication of assets Yes Yes Selective album(s) for backup Yes N/A Download photos and videos to local device Yes Yes Multi-user support Yes Yes Album and Shared albums Yes Yes Scrubbable/draggable scrollbar Yes Yes Support raw formats Yes Yes Metadata view (EXIF, map) Yes Yes Search by metadata, objects, faces, and CLIP Yes Yes Administrative functions (user management) No Yes Background backup Yes N/A Virtual scroll Yes Yes OAuth support Yes Yes API Keys N/A Yes LivePhoto/MotionPhoto backup and playback Yes Yes Support 360 degree image display No Yes User-defined storage structure Yes Yes Public Sharing Yes Yes Archive and Favorites Yes Yes Global Map Yes Yes Partner Sharing Yes Yes Facial recognition and clustering Yes Yes Memories (x years ago) Yes Yes Offline support Yes No Read-only gallery Yes Yes Stacked Photos Yes Yes Tags No Yes Folder View Yes Yes Translations Read more about translations here. Repository activity Star history Contributors (Preview — first 8 000 chars. View full README ↗) #14 chthollyphile / folia-major 专注于绚丽的歌词动画效果的本地音乐/navidrome/第三方网易云播放器 TypeScript ⭐ 915 🍴 58 ⭐ 319 stars today 📖 README # Folia Lyrics Reimagined // 辞曲新境 [](https://github.com/chthollyphile/folia-major/releases) [](https://github.com/chthollyphile/folia-major/blob/main/LICENSE) [](https://github.com/chthollyphile/folia-major/stargazers) [](https://nodejs.org/) [](#contributors-) [桌面版下载](https://github.com/chthollyphile/folia-major/releases) · [Vercel 部署](https://vercel.com/new/clone?repository-url=https://github.com/chthollyphile/folia-major) · [使用指南](https://folia-site.vercel.app/guide/) · [技术说明](docs/technical.md) 项目简介 Folia是一个以全屏沉浸式歌词播放为核心的在线音乐播放器，支持网易云，navidrome和本地音乐库，通过智能歌词匹配，AI生成配色主题，以及多种全屏歌词动画为用户提供独特的听歌体验。 如果你希望直接开箱即用，马上体验，推荐直接使用基于Electron的 windows/ macOS/ Linux 桌面端版本。 如果希望能够在移动设备上使用，或在浏览器上体验云端多平台，可以选择一键部署到 Vercel 的 Web 版本，或自行部署到其他支持 Node.js 的平台。 展示 演示视频 https://github.com/user-attachments/assets/fd27f4f0-64b9-4c57-8c3b-10df767f934b https://github.com/user-attachments/assets/704f195a-2194-434b-86e8-8f36290e5cc4 主题预览 浮名 流光 心象 云阶 群唱 倾诉 不同的歌词动画具有不同的排版氛围和可调参数，让全屏歌词拥有如同文字PV般的丰富视觉效果，同时又能兼顾响应式布局，自动适配不同窗口尺寸。 核心能力 模块 说明 在线搜索与播放 搜索歌曲、歌手或专辑后即可播放，并自动加载相关封面与歌词。 本地音乐支持 可导入本地音频文件，在本地安全保存索引信息，不上传文件内容。 智能歌词匹配 本地歌曲可自动匹配在线歌词与封面，也支持手动修正匹配结果。 LRC 文件识别 自动加载同目录同名 .lrc 歌词文件，或歌词文件内嵌lrc歌词。适配 LDDC 生成的增强型逐字歌词格式 Now Playing 接入 支持通过本机 Now Playing 服务接入外部播放器的歌曲、时间轴与歌词信息，并驱动 Folia 的舞台视图与全屏歌词渲染。 AI 主题生成 基于歌曲情绪与歌词内容生成沉浸式背景与视觉参数。 多端体验 提供 Web 部署方式，同时支持桌面端打包分发。 桌面端下载 桌面版内置前后端运行环境，适合希望即装即用的用户。最新版本请前往 Releases 页面。 Linux 包、Wayland / Hyprland 遥控窗和桌面端细节见 技术与开发说明。 文档与开发 更完整的使用说明请访问 Folia Guide。 部署、环境变量、本地开发、Stage API、常用脚本和技术栈见 技术与开发说明。 如果你希望快速上线 Web 版本，请阅读 Vercel 一键部署指南 来创建项目 本地音乐与匹配说明 使用本地音乐时，Folia 会优先尝试从以下来源补全信息： 音频文件自身元数据 同目录同名歌词文件 在线匹配结果 如果自动匹配不准确，可以在播放界面的右侧面板进入“本地”选项卡，手动搜索并指定更合适的歌词、封面或元数据来源。你也可以选择只使用本地信息，关闭在线匹配结果。 贡献者 Thanks goes to these wonderful people. Issue reports, bug reports, ideas, docs, design, tests, and code are all counted through the all-contributors spec. 冬霧 💻 zhao_alpha 🐛 hz1ang 🐛 🤔 steadyoak 🐛 🤔 POINTER 🐛 🤔 Yuki-3939 🤔 MewsCat 🐛 🤔 tumuyan 🐛 🤔 💻 948720857 🐛 谦君 (Preview — first 8 000 chars. View full README ↗) #15 mattpocock / skills Skills for Real Engineers. Straight from my .claude directory. Shell ⭐ 156,038 🍴 13,431 ⭐ 1,289 stars today 📖 README Skills For Real Engineers My agent skills that I use every day to do real engineering - not vibe coding. Developing real applications is hard. Approaches like GSD, BMAD, and Spec-Kit try to help by owning the process. But while doing so, they take away your control and make bugs in the process hard to resolve. These skills are designed to be small, easy to adapt, and composable. They work with any model. They're based on decades of engineering experience. Hack around with them. Make them your own. Enjoy. If you want to keep up with changes to these skills, and any new ones I create, you can join ~60,000 other devs on my newsletter: Sign Up To The Newsletter Quickstart (30-second setup) Run the skills.sh installer: npx skills@latest add mattpocock/skills Pick the skills you want, and which coding agents you want to install them on. Make sure you select /setup-matt-pocock-skills. Run /setup-matt-pocock-skills in your agent. It will: Ask you which issue tracker you want to use (GitHub, Linear, or local files) Ask you what labels you apply to tickets when you triage them (/triage uses labels) Ask you where you want to save any docs we create Bam - you're ready to go. Why These Skills Exist I built these skills as a way to fix common failure modes I see with Claude Code, Codex, and other coding agents. #1: The Agent Didn't Do What I Want "No-one knows exactly what they want" David Thomas & Andrew Hunt, The Pragmatic Programmer The Problem. The most common failure mode in software development is misalignment. You think the dev knows what you want. Then you see what they've built - and you realize it didn't understand you at all. This is just the same in the AI age. There is a communication gap between you and the agent. The fix for this is a grilling session - getting the agent to ask you detailed questions about what you're building. The Fix is to use: /grill-me - for non-code uses /grill-with-docs - same as /grill-me, but adds more goodies (see below) These are my most popular skills. They help you align with the agent before you get started, and think deeply about the change you're making. Use them every time you want to make a change. #2: The Agent Is Way Too Verbose With a ubiquitous language, conversations among developers and expressions of the code are all derived from the same domain model. Eric Evans, Domain-Driven-Design The Problem: At the start of a project, devs and the people they're building the software for (the domain experts) are usually speaking different languages. I felt the same tension with my agents. Agents are usually dropped into a project and asked to figure out the jargon as they go. So they use 20 words where 1 will do. The Fix for this is a shared language. It's a document that helps agents decode the jargon used in the project. Example Here's an example [`CONTEXT.md`](https://github.com/mattpocock/course-video-manager/blob/076a5a7a182db0fe1e62971dd7a68bcadf010f1c/CONTEXT.md), from my `course-video-manager` repo. Which one is easier to read? - **BEFORE**: "There's a problem when a lesson inside a section of a course is made 'real' (i.e. given a spot in the file system)" - **AFTER**: "There's a problem with the materialization cascade" This concision pays off session after session. This is built into /grill-with-docs. It's a grilling session, but that helps you build a shared language with the AI, and document hard-to-explain decisions in ADR's. It's hard to explain how powerful this is. It might be the single coolest technique in this repo. Try it, and see. [!TIP] A shared language has many other benefits than reducing verbosity: Variables, functions and files are named consistently, using the shared language As a result, the codebase is easier to navigate for the agent The agent also spends fewer tokens on thinking, because it has access to a more concise language #3: The Code Doesn't Work "Always take small, deliberate steps. The rate of feedback is your speed limit. Never take on a task that’s too big." David Thomas & Andrew Hunt, The Pragmatic Programmer The Problem: Let's say that you and the agent are aligned on what to build. What happens when the agent still produces crap? It's time to look at your feedback loops. Without feedback on how the code it produces actually runs, the agent will be flying blind. The Fix: You need the usual tranche of feedback loops: static types, browser access, and automated tests. For automated tests, a red-green-refactor loop is critical. This is where the agent writes a failing test first, then fixes the test. This helps give the agent a consistent level of feedback that results in far better code. I've built a /tdd skill you can slot into any project. It encourages red-green-refactor and gives the agent plenty of guidance on what makes good and bad tests. For debugging, I've also built a /diagnosing-bugs skill that wraps best debugging practices into a simple loop. #4: We Built A Ball Of Mud "Invest in the design of the system every day." Kent Beck, Extreme Programming Explained "The best modules are deep. They allow a lot of functionality to be accessed through a simple interface." John Ousterhout, A Philosophy Of Software Design The Problem: Most apps built with agents are complex and hard to change. Because agents can radically speed up coding, they also accelerate software entropy. Codebases get more complex at an unprecedented rate. The Fix for this is a radical new approach to AI-powered development: caring about the design of the code. This is built in to every layer of these skills: /to-prd quizzes you about which modules you're touching before creating a PRD And crucially, /improve-codebase-architecture helps you rescue a codebase that has become a ball of mud. I recommend running it on your codebase once every few days. Summary Software engineering fundamentals matter more than ever. These skills are my best effort at condensing these fundamentals into repeatable practices, to help you ship the best apps of your career. Enjoy. Reference These split on one axis — who can invoke them. User-invoked skills are reachable only when you type them (e.g. /grill-me); their job is to orchestrate. Model-invoked sk (Preview — first 8 000 chars. View full README ↗) #16 CoplayDev / unity-mcp Unity MCP acts as a bridge between AI assistants and your Unity Editor. Give your LLM tools to manage assets, control scenes, edit scripts, and automate tasks within Unity. C# ⭐ 11,364 🍴 1,247 ⭐ 49 stars today 📖 README [English](README.md) [简体中文](docs/i18n/README-zh.md)    |    [Discord](https://discord.gg/y4p8KfzrN4) [Wiki](https://coplaydev.github.io/unity-mcp/) #### Proudly sponsored and maintained by [Aura](https://www.tryaura.dev/) — the AI assistant for Unreal & Unity. ##### And don't miss [Godot AI](https://github.com/hi-godot/godot-ai), the new open source project from the makers of MCP for Unity. Create your Unity apps with LLMs. MCP for Unity bridges AI assistants — Claude, Codex, VS Code, local LLMs, and more — with your Unity Editor via Model Context Protocol. Give your LLM the tools to manage assets, control scenes, edit scripts, run tests, and automate your game dev workflows. Recent Updates * **[v10.0.0](https://github.com/CoplayDev/unity-mcp/releases/tag/v10.0.0)** (2026-06-30) * **[v9.7.3](https://github.com/CoplayDev/unity-mcp/releases/tag/v9.7.3)** (2026-06-15) * **[v9.7.1](https://github.com/CoplayDev/unity-mcp/releases/tag/v9.7.1)** (2026-05-24) * **[v9.7.0](https://github.com/CoplayDev/unity-mcp/releases/tag/v9.7.0)** (2026-05-22) * **[v9.6.8](https://github.com/CoplayDev/unity-mcp/releases/tag/v9.6.8)** (2026-04-27) Full history: [Release Notes](https://coplaydev.github.io/unity-mcp/releases). What it does Control the Unity Editor in natural language from any MCP client — create scenes & GameObjects, edit C# scripts, manage assets, run tests, profile, and build. 47 focused MCP tool entrypoints, any client, free & MIT. Browse the full tool catalog → Quickstart Requirements: Unity 2021.3 LTS → 6.x · Python 3.10+ (via uv). Works with any MCP client — Claude Desktop & Code, Cursor, VS Code, Windsurf, Cline, Gemini CLI, and more. Install — Unity → Package Manager → Add from git URL: https://github.com/CoplayDev/unity-mcp.git?path=/MCPForUnity#main  (pin #v10.0.0 for this release, or openupm add com.coplaydev.unity-mcp) Configure — Window → MCP for Unity → Configure All Detected Clients. Prompt — "Create a cube at the origin and add a Rigidbody." The cube appears in seconds. Community Discord — chat with maintainers and other contributors Issues — bugs and feature requests Discussions — design ideas and broader questions Security: see SECURITY.md for private reporting Contributing See CONTRIBUTING.md. Branch off beta, not main. The full dev setup, testing, and release process live in the Contributing docs. Advanced Multiple Unity instances — Multi-Instance Routing Tool groups (vfx / animation / ui / testing / etc.) — Tool Groups v10 asset generation and upgrade notes — v10 Migration Roslyn script validation — Roslyn Validation Remote-hosted server with auth — Remote Server Auth Star History Citation If MCP for Unity helped your research, please cite it. @inproceedings{wu2025mcpunity, author = {Wu, Shutong and Barnett, Justin P.}, title = {{MCP-Unity}: {Protocol-Driven} Framework for Interactive {3D} Authoring}, year = {2025}, isbn = {9798400721366}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/3757376.3771417}, doi = {10.1145/3757376.3771417}, series = {SA Technical Communications '25} } Unity AI Tools by Aura Aura offers 2 AI tools for Unity: - MCP for Unity is available freely under the MIT license. - Aura for Unity is a premium Unity/Unreal AI assistant built for game devs. Disclaimer This project is a free and open-source tool for the Unity Editor, and is not affiliated with Unity Technologies. License: MIT — see LICENSE. (Preview — first 8 000 chars. View full README ↗) #17 alirezarezvani / claude-skills 337 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 330+ skills, customizable references, scripts)for Claude Code, Codex, Gemini CLI, Cursor, and 8 more coding agents — engineering, marketing, product, compliance, C-level advisory, research, business operations, commercial & finance, and your daily productivity skills. Python ⭐ 19,912 🍴 2,734 ⭐ 130 stars today 📖 README Claude Code Skills & Plugins — Agent Skills for Every Coding Tool 354 production-ready Claude Code skills, plugins, and agent skills for 13 AI coding tools. The most comprehensive open-source library of Claude Code skills and agent plugins — also works with OpenAI Codex, Gemini CLI, Cursor, and 9 more coding agents. Reusable expertise packages covering engineering, DevOps, marketing (incl. AEO — Answer Engine Optimization for LLM citation), security (PreToolUse hooks), compliance, C-level advisory (incl. founder-mode CFO/CMO/CRO/CPO/COO/CHRO/CISO/GC/CDO/CAIO/CCO/VPE personas + 21 /cs:* slash commands), productivity (capture/email/reflect), an academic research stack (litreview/grants/dossier/patent/syllabus/pulse/notebooklm/deep-research + hybrid router), and enterprise Research Operations (clinical-research/research-finance/market-research/product-research, v2.9.0). Works with: Claude Code · OpenAI Codex · Gemini CLI · OpenClaw · Hermes Agent[^hermes] · Mistral Vibe[^vibe] · Cursor · Aider · Windsurf · Kilo Code · OpenCode · Augment · Antigravity [^hermes]: Hermes Agent is BYO-sync tier: the repo ships a pre-generated .hermes/skills/claude-skills/ tree, but you run python scripts/sync-hermes-skills.py once locally to install into ~/.hermes/skills/. Uses the same agentskills.io SKILL.md standard — no format conversion. [^vibe]: Mistral Vibe is also BYO-sync tier: the repo ships a pre-generated .vibe/skills/claude-skills/ tree, run ./scripts/vibe-install.sh once locally to install into ~/.vibe/skills/. Same agentskills.io SKILL.md standard — no format conversion. Docs: https://docs.mistral.ai/mistral-vibe/agents-skills. 5,200+ GitHub stars — the most comprehensive open-source Claude Code skills & agent plugins library. What Are Claude Code Skills & Agent Plugins? Claude Code skills (also called agent skills or coding agent plugins) are modular instruction packages that give AI coding agents domain expertise they don't have out of the box. Each skill includes: SKILL.md — structured instructions, workflows, and decision frameworks Python tools — 593 CLI scripts (all stdlib-only, zero pip installs) Reference docs — 711 templates, checklists, and domain-specific knowledge files One repo, thirteen platforms. Works natively as Claude Code plugins, Codex agent skills, Gemini CLI skills, Hermes Agent skills, Mistral Vibe skills, and converts to more tools via scripts/convert.sh. All 593 Python tools run anywhere Python runs. Skills vs Agents vs Personas Skills Agents Personas Purpose How to execute a task What task to do Who is thinking Scope Single domain Single domain Cross-domain Voice Neutral Professional Personality-driven Example "Follow these steps for SEO" "Run a security audit" "Think like a startup CTO" All three work together. See Orchestration for how to combine them. Quick Install Gemini CLI (New) # Clone the repository git clone https://github.com/alirezarezvani/claude-skills.git cd claude-skills # Run the setup script ./scripts/gemini-install.sh # Start using skills > activate_skill(name="senior-architect") Claude Code (Recommended) # Add the marketplace /plugin marketplace add alirezarezvani/claude-skills # Install by domain /plugin install engineering-skills@claude-code-skills # 24 core engineering /plugin install engineering-advanced-skills@claude-code-skills # 25 POWERFUL-tier /plugin install product-skills@claude-code-skills # 12 product skills /plugin install marketing-skills@claude-code-skills # 43 marketing skills /plugin install ra-qm-skills@claude-code-skills # 12 regulatory/quality /plugin install pm-skills@claude-code-skills # 6 project management /plugin install c-level-skills@claude-code-skills # 28 C-level advisory (full C-suite) /plugin install business-growth-skills@claude-code-skills # 4 business & growth /plugin install finance-skills@claude-code-skills # 2 finance (analyst + SaaS metrics) # Or install individual skills /plugin install skill-security-auditor@claude-code-skills # Security scanner /plugin install playwright-pro@claude-code-skills # Playwright testing toolkit /plugin install self-improving-agent@claude-code-skills # Auto-memory curation /plugin install content-creator@claude-code-skills # Single skill OpenAI Codex npx agent-skills-cli add alirezarezvani/claude-skills --agent codex # Or: git clone + ./scripts/codex-install.sh OpenClaw bash <(curl -s https://raw.githubusercontent.com/alirezarezvani/claude-skills/main/scripts/openclaw-install.sh) Manual Installation git clone https://github.com/alirezarezvani/claude-skills.git # Copy any skill folder to ~/.claude/skills/ (Claude Code) or ~/.codex/skills/ (Codex) Multi-Tool Support (New) Convert all 345 skills to 9 AI coding tools with a single script: Tool Format Install Cursor .mdc rules ./scripts/install.sh --tool cursor --target . Aider CONVENTIONS.md ./scripts/install.sh --tool aider --target . Kilo Code .kilocode/rules/ ./scripts/install.sh --tool kilocode --target . Windsurf .windsurf/skills/ ./scripts/install.sh --tool windsurf --target . OpenCode .opencode/skills/ ./scripts/install.sh --tool opencode --target . Augment .augment/rules/ ./scripts/install.sh --tool augment --target . Antigravity ~/.gemini/antigravity/skills/ ./scripts/install.sh --tool antigravity Hermes Agent ~/.hermes/skills/ python scripts/sync-hermes-skills.py --verbose Mistral Vibe ~/.vibe/skills/ ./scripts/vibe-install.sh How it works: # 1. Convert all skills to all tools (takes ~15 seconds) ./scripts/convert.sh --tool all # 2. Install into your project (with confirmation) ./scripts/install.sh --tool cursor --target /path/to/project # Or use --force to skip confirmation: ./scripts/install.sh --tool aider --target . --force # 3. Verify find .cursor/rules -name "*.mdc" | wc -l # Should show 346 Each tool gets: - ✅ All 345 skills converted to native format - ✅ Per-tool README with install/verify/update steps - ✅ Support for scripts, references, templates where applicable - ✅ Zero manual conversion work Run ./scripts/convert.sh --tool all to generate tool-specific outputs locally. Skills Overview 354 skills across 18 domains: Domain Skills Highlights Details 🔧 Engineering — Core 52 Architecture, frontend, backend, fullstack, QA, DevOps, SecOps, AI/ML, data, Playwright Pro (test gen, flaky fix, migrations), self-improving agent (auto-memory curation), security suite, a11y audit, named-persona-adversarial-review (review via named engineering philosophies) [engineering-team/](engineerin (Preview — first 8 000 chars. View full README ↗) #18 crynta / terax-ai Lightweight (7MB) Terminal-first AI-native dev workspace TypeScript ⭐ 7,903 🍴 856 ⭐ 44 stars today 📖 README Terax Lightweight Terminal-first AI-native dev workspace. Website · Docs · Website's source code Terax is a lightweight open-source terminal (ADE) built on Tauri 2 + Rust and React 19. A native PTY backend with a WebGL renderer, an agentic AI side-panel that runs against your own keys or fully local models, plus a code editor, file explorer, source control with a git graph, and a web preview pane built in. About 7-8 MB on disk. No telemetry. No account. Screenshots Multi-tab terminal with WebGL rendering Custom themes, presets, and background images Web preview of local dev servers Source control panel with git graph in history Agentic AI workflow with edit diffs in the code editor Features Terminal xterm.js with WebGL renderer, multi-tab with background streaming GPU-accelerated block-based terminal with editor-like command input Native PTY backend via portable-pty (zsh, bash, pwsh, fish, cmd) Split panels (horizontal and vertical) Inline search, link detection, true-color Per-tab workspace environments on Windows (Local, or any installed WSL distro) Code editor CodeMirror 6 (supports all popular languages - TS/JS, Rust, Python, Go, C/C++, Java, HTML/CSS, JSON, Markdown, etc.) Inline AI autocomplete with local model support AI edit diffs, accept or reject hunk by hunk Vim mode Ten built-in editor themes: Atom One, Aura, Copilot, GitHub Dark / Light, Gruvbox Dark, Nord, Tokyo Night, Xcode Dark / Light Source control Stage / unstage hunks, commit (Cmd+Enter / Ctrl+Enter), push with upstream awareness Branch display including detached HEAD state Git history pane with a real commit graph (lane rendering for merges and branches) Commit search and filter, click through to the remote commit page File explorer Catppuccin icon theme Fuzzy search, keyboard navigation, inline rename, context actions Attach files and selections directly to the AI side-panel Web preview Auto-detects local dev servers and opens them in a preview tab External URL preview via a native child webview Themes and customization Custom themes built in-app, switch between bundled presets and your own Create your own themes, share them or import from the community Background images with adjustable opacity and blur Editor theme is independent from the app theme AI BYOK providers: OpenAI, Anthropic, Google (Gemini), Groq, xAI (Grok), Cerebras, OpenRouter, DeepSeek, Mistral, plus any OpenAI-compatible endpoint Local / offline: LM Studio, MLX, Ollama Agentic workflow: plans, sub-agents, project memory via TERAX.md, file read / write / edit / multi-edit / grep / glob, bash with approval gating, background processes Composer: snippets via #handle, files via @path, slash commands, voice input, attach-to-agent from explorer or selection Custom agents with their own system prompt and tool subset Plan mode for multi-step work, generates and confirms before doing Install Latest installers are on the Releases page. Terax auto-updates from there. Windows notes On first launch Windows shows "Windows protected your PC" because Terax isn't code-signed yet. Click More info then Run anyway. Default shell detection: pwsh.exe (PowerShell 7+) -> powershell.exe (Windows PowerShell 5.1) -> cmd.exe. WSL is a first-class workspace environment, not a wrapped subprocess. Linux notes Arch / AUR: yay -S terax-bin (or paru, etc.). Tracks the latest release. NixOS / Nix: use the official flake — nix profile install github:crynta/terax-ai (non-NixOS), or import the flake and add inputs.terax.packages.${pkgs.system}.terax to environment.systemPackages (NixOS). The nixosModules.terax output is also available for a simpler setup. AppImage: needs FUSE. Without it: ./Terax_*.AppImage --appimage-extract-and-run. On Wayland with rendering glitches, try WEBKIT_DISABLE_DMABUF_RENDERER=1. Otherwise the .deb / .rpm packages link against the system GTK stack and tend to be smoother. Configure AI Open Settings -> AI. Pick a provider and paste your API key. For local inference, point Terax at your LM Studio / MLX / Ollama endpoint. Keys are written to the OS keychain via keyring. They never touch disk or localStorage. Build from source Prerequisites - Rust (stable), https://rustup.rs - Node 20+ and pnpm - Tauri prerequisites for your platform, https://tauri.app/start/prerequisites/ Run pnpm install pnpm tauri dev # development pnpm tauri build # production bundle Checks pnpm exec tsc --noEmit # frontend type-check cd src-tauri && cargo clippy --all-targets --locked -D warnings # Rust lint (matches CI) cd src-tauri && cargo test --locked # Rust tests Tech stack Tauri 2, Rust, portable-pty, React 19, TypeScript, Vite, xterm.js, CodeMirror 6, Vercel AI SDK v6, Tailwind v4, shadcn/ui, Zustand. Contributing Issues and PRs are welcome! Feel free to open issues, suggest features, or submit pull requests. See CONTRIBUTING.md for more details. License Terax is licensed under the Apache-2.0 License. For more information on our dependencies, see Apache License 2.0. Star history (Preview — first 8 000 chars. View full README ↗)