Read-only repo analysis -> one CODE.md file

Supercharge your LLM with CODE.md.

codemd.dev analyzes your repository and generates CODE.md: a factual map of your architecture, file relationships, code flows, and UI graph. Drop it into your source branch or repo so Codex, Claude, Cursor, Copilot, and other AI coding agents start with the truth before they edit. Less time rediscovering the codebase. Fewer wasted prompts. Faster answers. Smarter use of your LLM budget.

Search Source Code Repository See how CODE.md works
No training required. No runtime access needed. No LLM summaries required for the truth layer.
codemd.dev page explaining that AI coding assistants are only as good as the context they start with.

Your AI coding agent is only as good as the context it starts with.

Most AI coding tools are powerful, but they still start each task by searching and guessing. CODE.md gives them a factual starting map of your repository before the first prompt.

Without CODE.md

The agent starts cold and has to discover your repo while answering.

  • xOpens many files before finding the right one.
  • xMisses important dependencies and change impact.
  • xGives generic answers that sound right but may not fit your code.
  • xSpends more turns narrowing down what your team already knows.

With CODE.md

The agent starts with a repo map generated from actual code evidence.

  • ✓Finds core files, entry points, routes, UI surfaces, and TODOs faster.
  • ✓Understands callgraph and file dependency relationships up front.
  • ✓Answers with more repo-specific context and less guessing.
  • ✓Helps developers review, debug, onboard, and change code with more confidence.
Use your LLM budget on engineering work, not repeated repo discovery.

If your team spends thousands per month on AI coding tools, even a small reduction in repeated repo-discovery work can matter. CODE.md helps make those AI sessions more efficient by giving the model high-signal context upfront.

How codemd.dev gives every repo its CODE.md

codemd.dev does not need to run your app. It reads the repository, extracts structure, and generates a file your AI agent can use immediately.

1

Connect or upload

Allow codemd.dev to run read-only analysis on a GitHub repo, or upload a code archive.

2

codemd.dev maps the repo

It extracts routes, files, functions, callgraphs, UI elements, TODOs, dependencies, and source inventory.

3

You get CODE.md

A single machine-readable file summarizes the structure and evidence found in the repository.

4

Drop it into the repo

Put CODE.md in your source branch so your AI coding agent has context in every coding session.

"CODE.md helps because it gives me a factual starting map before I search, explain, or edit."

Codex, explaining why one generated repo map improves AI coding work. Like design.md gives agents product and design context, CODE.md gives agents codebase structure and evidence.
AI coding assistant diagram saying every repository needs CODE.md.

What CODE.md contains

A useful CODE.md is not a marketing summary. It is a factual repo briefing generated from actual analysis.

Repository overviewMain languages, structure, source inventory, and what was actually analyzed.
Architecture mapEntry points, modules, core files, file dependencies, and callgraph relationships.
UI and routesButtons, forms, links, pages, API routes, and where user-facing behavior connects to code.
Known gapsTODOs and unfinished work signals directly extracted from developer-authored code comments.
Risk signalsHighly connected functions, dependency hotspots, recent changes, and code areas to treat carefully.
Evidence policyWhat was found, what was unavailable, and where the agent should avoid speculation.

Give your AI the map it needs.

Run codemd.dev analysis, generate CODE.md, and add it to your repository so every AI coding session starts with real code context.

Generate CODE.md for your repo