Codex CLI

About

Key Features

• Run `codex` on your machine → get a locally-running coding agent for project work
• Paste a task definition → the agent executes steps and builds a working project
• Point it at framework documentation (via GitMCP) → it learns APIs and applies them correctly
• Install in VS Code/Cursor/Windsurf → use the agent inside your preferred editor
• Sign in with a ChatGPT plan or API key → use your existing OpenAI access without extra setup

Use Cases

• A full-stack engineer building a CSV viewer in a new web framework using only the framework’s docs and a task brief
• A VS Code user wiring up features in a TypeScript project while keeping the agent local and authenticated with a ChatGPT Plus plan

Try It Like This

1. 1
   Build a CSV viewer in an unfamiliar web framework

   Write a short task definition that describes UI, import/export, and validation → run codex in the project root and paste the task definition so the agent can read it and fetch framework docs via GitMCP → review the generated files, run the dev server, and ask codex to iterate on UX or bug fixes.

2. 2
   Wire a TypeScript feature inside VS Code

   Install codex via npm or Homebrew and sign in with your ChatGPT plan or provide an API key → open the repo in VS Code where the Codex extension or integration is available and paste a task like 'add search to the items list' → inspect the proposed edits, accept diffs, and let codex apply the changes across files while preserving project conventions.

3. 3
   Refactor a backend field across a Django project

   Run codex from the repository root and give a task: 'rename field X to Y everywhere and update migrations' → allow codex to analyze the codebase and present a diff showing model, migration, and usage changes → review tests and run them locally, then ask codex to create or update any failing tests.

4. 4
   Integrate a third-party API using only docs

   Paste the API task brief and point codex at the API docs (via a GitMCP endpoint or local docs) → codex reads the docs, scaffolds authentication code and request helpers, and generates example usage and error handling → test the integration locally and ask codex to harden retry/backoff logic or types.

5. 5
   Onboard to a large unfamiliar repo and add a small feature

   Start codex in the repo and provide a one-paragraph onboarding note describing code areas and desired feature → let codex explore README, CONTRIBUTING, and key modules to build context → request a small feature implementation, review the diff, and ask follow-up questions to clarify design choices.

Pros & Cons

Getting Started

1. 1 Install with `npm i -g @openai/codex` or `brew install --cask codex`, or download a binary from the latest GitHub release.
2. 2 Run `codex` and choose Sign in with ChatGPT (or configure an API key).
3. 3 Paste a short task definition and let Codex start generating the project files and implementation steps.