What is AGENTS.md?
AGENTS.md is a repository instruction file that tells coding agents how to work inside a project: commands, conventions, architecture rules, and review expectations.
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Markdown
An AGENTS.md generator creates repository-specific instructions for AI coding agents. It captures commands, architecture rules, conventions, forbidden patterns, and review expectations in a file that can travel with the repo, giving tools such as Codex, Claude Code, Pi, or Hal clearer local context.
Enter your stack, package manager, test command, lint command, architecture rules, forbidden patterns, and preferred agent workflow. The tool generates a copy-ready instruction file for your repo.
AI coding agents can drift into patterns that do not match the codebase. A standards file gives each loop concrete local rules before implementation starts.
Favor instructions that change behavior: exact commands, source directories, migration rules, review expectations, and patterns the agent must avoid. Keep generic advice out unless it helps the agent make a concrete decision.
Commit the generated AGENTS.md, keep it short enough to maintain, and update it when review feedback reveals repeated agent mistakes.
Use this tool before a coding agent edits files. Then move from tool output into PRD-driven planning, a first Hal loop, or a review-before-merge checklist. Treat generated text as a draft and verify it against the repository before use.
Before adopting Hal, inspect the source repository, install guide, pricing page, and machine-readable pricing. This tool does not guarantee code quality, test success, or merge safety.
Short answers before you hand the output to an agent workflow.
AGENTS.md is a repository instruction file that tells coding agents how to work inside a project: commands, conventions, architecture rules, and review expectations.
Yes. Hal's project standards workflow is designed to give each implementation loop repo-specific rules and context.
In most teams, yes. Committing the file makes agent instructions inspectable and repeatable across future coding loops.
Prepare better PRDs, stories, and standards before an agent touches the repo.
analyzer
Check whether a product requirement is specific enough for an AI coding loop before an agent touches the repo.
generator
Generate a markdown PRD, user stories, acceptance criteria, and a Hal-ready planning prompt from a feature idea.
analyzer
Break a feature request into reviewable implementation stories and score whether it is safe for an AI coding loop.
Next step
Hal is a terminal-first CLI for PRD-native coding loops. Use the generated markdown as planning input, keep the work bounded, and review agent output before merging.