LuD1161

name	description	user_invocable
codex-review	Send the current plan to OpenAI Codex CLI for iterative review. Claude and Codex go back-and-forth until Codex approves the plan.	true

Codex Plan Review (Iterative)

Send the current implementation plan to OpenAI Codex for review. Claude revises the plan based on Codex's feedback and re-submits until Codex approves. Max 5 rounds.

OmerFarukOruc

AI Coding Agent Guidelines (claude.md)

These rules define how an AI coding agent should plan, execute, verify, communicate, and recover when working in a real codebase. Optimize for correctness, minimalism, and developer experience.

---

Operating Principles (Non-Negotiable)

• Correctness over cleverness: Prefer boring, readable solutions that are easy to maintain.
• Smallest change that works: Minimize blast radius; don't refactor adjacent code unless it meaningfully reduces risk or complexity.

miklschmidt

How to use:

1. Clone https://github.com/miklschmidt/codex and build codex yourself.
   • i've added devenv in my fork, you can try devenv shell nix build .#packages.<system>.codex-rs (eg. devenv shell nix build .#packages.x86_64-linux.codex-rs)
   • when built, symlink the binary to ~/.local/bin/codex: ln -s $(pwd)/result/bin/codex ~/.local/bin/codex
2. Add the instructions (.md files) from this gist to .codex/ in the project where you want to test it.
3. Launch codex --profile orchestrator and ask it to do something.

SamSaffron

Claude Agent SDK Technical Specification

Version: 1.0.0 Protocol Version: 2024-11-05 Last Updated: 2026-01-10

Table of Contents

1. Overview
2. Architecture

awni

The following guide will show you how to connect a local model served with MLX to OpenCode for local coding.

1. Install OpenCode

curl -fsSL https://opencode.ai/install | bash

2. Install mlx-lm

mizchi

/**
 * My Portable RAG
 * $ pnpm add sqlite-vec @ai-sdk/google ai
 * SQLite Vector Search + Google AI Embeddings
 *
 * Required environment variables:
 *   GOOGLE_GENERATIVE_AI_API_KEY=your-api-key
 *
 * Usage:
 *   # Index text content

wong2

Task

Launch a new agent that has access to the following tools: Bash, Glob, Grep, LS, exit_plan_mode, Read, Edit, MultiEdit, Write, NotebookRead, NotebookEdit, WebFetch, TodoRead, TodoWrite, WebSearch. When you are searching for a keyword or file and are not confident that you will find the right match in the first few tries, use the Agent tool to perform the search for you.

When to use the Agent tool:

• If you are searching for a keyword like "config" or "logger", or for questions like "which file does X?", the Agent tool is strongly recommended

When NOT to use the Agent tool:

• If you want to read a specific file path, use the Read or Glob tool instead of the Agent tool, to find the match more quickly
• If you are searching for a specific class definition like "class Foo", use the Glob tool instead, to find the match more quickly
• If you are searching for code within a specific file or set of 2-3 files, use the Read tool instead of the Agent tool, to find the match more quickly

azu

export const requireComment = {
  meta: {
    type: "suggestion",
    docs: {
      description: "useEffectにはコメントでの説明が必須です。",
    },
    schema: [],
    messages: {
      requireCommentOnUseEffect: `useEffectにはコメントでの説明が必須です。

awni

"""
A minimal, fast example generating text with Llama 3.1 in MLX.

To run, install the requirements:

    pip install -U mlx transformers fire

Then generate text with:

    python l3min.py "How tall is K2?"

veekaybee

Anti-hype LLM reading list

Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.

Foundational Concepts

Pre-Transformer Models