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Ai Codex

Generate a compact codebase index for AI assistants — saves 50K+ tokens per conversation

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Works With

Claude CodeCursorWindsurfVS CodeDeveloper tool

About

ai-codex

](https://claude.ai/code) [ [](https://www.typescriptlang.org/)

This project was entirely designed, written, and published by [Claude Code](https://claude.ai/code) (Anthropic's AI coding assistant). The concept, implementation, documentation, and examples were all generated in a single conversation session.

Generate a compact codebase index that gives AI coding assistants instant context about your project structure. Instead of wasting 50K+ tokens on file exploration at the start of every conversation, your AI assistant reads a pre-built index and gets to work immediately.

Why

Every time you start a conversation with an AI coding assistant (Claude Code, Cursor, GitHub Copilot, etc.), it spends thousands of tokens exploring your codebase -- reading files, scanning directories, building a mental model. This happens every single conversation.

ai-codex solves this by generating compact, structured reference files that capture:

  • Every API route with its HTTP methods
  • Every page with its rendering strategy (client vs. server)
  • Every library function signature
  • Your database schema (key fields, relationships)
  • Your component tree with props

The result: 5 small files that replace 50K+ tokens of exploration, every time.

Quick Start

Run it in your project root:

bash
npx ai-codex

That's it. It auto-detects your framework and generates the index.

Output

By default, files are written to .ai-codex/ in your project root:

FileWhat it contains
routes.mdAPI routes grouped by resource, with HTTP methods
pages.mdPage tree with client/server rendering tags
lib.mdLibrary exports -- function signatures, classes
schema.mdDatabase schema -- key fields, FKs, relationships
components.mdComponent index with props, grouped by feature

Files that don't apply are skipped (e.g., no schema.md if you don't use Prisma).

Configuration

CLI Flags

bash
npx ai-codex --output .claude/codex     # custom output directory
npx ai-codex --include src lib           # only scan these directories
npx ai-codex --exclude tests __mocks__   # skip these directories
npx ai-codex --schema prisma/schema.prisma  # explicit schema path

Config File

Create a codex.config.json in your project root:

json
{
  "output": ".ai-codex",
  "include": ["src", "lib", "app"],
  "exclude": ["tests", "__mocks__"],
  "schema": "prisma/schema.prisma"
}

CLI flags override config file values.

Output Format Examples

routes.md

## products
GET,POST     /api/products [auth,db]
GET,PUT,DELETE /api/products/:id [auth,db]
POST         /api/products/:id/images [auth]

## orders
GET,POST     /api/orders [auth,db]
GET          /api/orders/:id [auth,db]
POST         /api/orders/:id/refund [auth,db]

Don't lose this

Three weeks from now, you'll want Ai Codex again. Will you remember where to find it?

Save it to your library and the next time you need Ai Codex, it’s one tap away — from any AI app you use. Group it into a bench with the rest of the team for that kind of task and you can pull the whole stack at once.

⚡ Pro tip for geeks: add a-gnt 🤵🏻‍♂️ as a custom connector in Claude or a custom GPT in ChatGPT — one click and your library is right there in the chat. Or, if you’re in an editor, install the a-gnt MCP server and say “use my [bench name]” in Claude Code, Cursor, VS Code, or Windsurf.

🤵🏻‍♂️

a-gnt's Take

Our honest review

This plugs directly into your AI and gives it new abilities it didn't have before. Generate a compact codebase index for AI assistants — saves 50K+ tokens per conversation. Once connected, just ask your AI to use it. It's completely free and works across most major AI apps. This one just landed in the catalog — worth trying while it's fresh.

Tips for getting started

1

Tap "Get" above, pick your AI app, and follow the steps. Most installs take under 30 seconds.

What's New

Version 1.0.06 days ago

Imported from GitHub

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