Best Tools to Generate CLAUDE.md and AGENTS.md Files

The best way to generate a CLAUDE.md or AGENTS.md depends on how much of your repository the generator can see. Claude Code's /init, OpenAI Codex and the GitHub Copilot cloud agent are fast starting points for a single repo. repowise is the pick when the file should reflect the dependency graph, git hotspots and recorded decisions, and stay current without anyone rewriting it.

The short list, as of October 2026:

• Claude Code /init: Anthropic's built-in generator for CLAUDE.md.
• OpenAI Codex: reads AGENTS.md in layers, from the git root down.
• GitHub Copilot cloud agent: generates repository instructions for Copilot.
• Cursor rules: project rules and AGENTS.md support, written by hand.
• Aider repo map: not a file generator, but a token-budgeted map worth copying from.
• repowise: writes CLAUDE.md and AGENTS.md from a code graph, git history and decisions.

For what these files are and what belongs in them, read the CLAUDE.md and AGENTS.md complete guide. This page covers the tools.

How we evaluated

We read each vendor's own documentation, fetched on 12 October 2026, and judged generators on four things.

• What it reads: the working tree only, or also the dependency graph, git history and decisions.
• What it writes: CLAUDE.md, AGENTS.md or another format, and whether hand-written content survives a rerun.
• How it stays fresh: one-time scaffold, or refreshed when the code changes.
• Who consumes it: which agents load the output.

Comparison table

Claude Code /init

Claude Code's /init analyzes your codebase and writes a starting CLAUDE.md with the build commands, test instructions and conventions it finds. If a file already exists it suggests improvements instead of overwriting it. Setting CLAUDE_CODE_NEW_INIT=1 turns it into a multi-phase flow that can also set up skills and hooks and shows a proposal before writing (Anthropic memory docs).

It shines on zero setup, and the output is in the exact shape Claude Code loads. Anthropic's guidance is to keep each file under 200 lines, use @path imports to organize a long file (imports still load at launch), and move rules for part of the codebase into path-scoped .claude/rules/. Claude Code also reads AGENTS.md when no CLAUDE.md exists.

Pick it if you use Claude Code, the repo is small to medium, and you will edit the result by hand.

OpenAI Codex

Codex treats AGENTS.md as its instruction file and walks from the git root to your working directory, concatenating files so closer directories take precedence (OpenAI Codex docs). Loading stops at project_doc_max_bytes, 32 KiB by default, so an oversized file is cut off.

Layered global, root and per-directory files suit monorepos. The format is an open standard, now stewarded by the Agentic AI Foundation under the Linux Foundation and read by more than twenty tools (agents.md).

Pick it if Codex is your main agent, or you want one format every tool can read.

GitHub Copilot cloud agent

GitHub can generate repository instructions from the Copilot cloud agent page, using a prompt aimed at fewer CI failures and less exploration: a codebase summary, build steps, test procedures and project layout. Output lives in .github/copilot-instructions.md, and Copilot also reads AGENTS.md, CLAUDE.md and GEMINI.md as agent instructions (GitHub docs).

Pick it if your team lives in GitHub Copilot and wants instructions committed next to path-specific .instructions.md files.

Cursor rules

Cursor gives you rules to write rather than a file generated from your code. Project rules live in .cursor/rules as .mdc files whose frontmatter controls when they apply (always, by glob, by description or by @-mention), and plain AGENTS.md is supported, including nested files. Cursor suggests keeping rules under 500 lines and referencing files instead of copying them (Cursor docs).

Its codebase index helps the editor retrieve context but is not a checked-in file. The Cursor comparison covers where indexing ends and checked-in context begins.

Pick it if you want glob-scoped editor rules alongside a shared AGENTS.md.

Aider repo map

Aider does not write an instruction file, but its repo map shows the right constraint: a concise map of classes, functions and signatures that fits a token budget set by --map-tokens (1k by default) (Aider docs). A good instruction file respects the same budget.

Pick it if you use Aider and want automatic, relevant context, or copy from the map when writing a file by hand.

repowise

repowise generates CLAUDE.md and AGENTS.md from its index, not from a model reading your files. repowise init builds the dependency graph, mines git history and records decisions. The file is then rendered from that data in well under a second, with no model call. Only the managed block is regenerated; anything you wrote outside the markers is preserved.

The managed section contains:

• an architecture summary and the top ten modules ranked by PageRank, with owners;
• entry points, ranked on execution-start evidence rather than fan-in;
• the detected tech stack and the build, test, lint and typecheck commands from package.json, pyproject.toml or Makefile;
• the five hottest files by churn percentile;
• up to eight active architectural decisions;
• a short workflow guide for when to call each of the ten MCP tools.

pip install repowise
repowise init                              # writes .claude/CLAUDE.md; add --agents for AGENTS.md
repowise generate-claude-md --stdout       # preview without writing
repowise generate-claude-md --workspace    # workspace-level file for multi-repo setups

repowise update refreshes the managed section after every change. The same intelligence is available live through MCP: get_why returns the recorded rationale behind a pattern, and get_change_risk scores a pending diff before merge. The file orients the agent; the tools answer the deeper questions. See the AI context layer, the architecture, or a generated example for FastAPI.

Pick it if the repo is large, several people or agents work in it, or you want a file that does not go stale after the next refactor.

How to choose

• Solo, small repo, Claude Code: run /init, then trim to under 200 lines.
• Codex or mixed agents: keep AGENTS.md as the single source and have CLAUDE.md import it with @AGENTS.md.
• GitHub Copilot team: generate Copilot instructions and keep AGENTS.md for other agents.
• Large or fast-moving repo, or a team: use repowise so hotspots, ownership and decisions stay current.
• Cursor user: add glob-scoped rules for subsystems and an AGENTS.md for the rest.

Whichever you pick, review the output. A generator can rank facts; it cannot decide what your team cares about.