AGENTS.md gives coding agents durable repository guidance: structure, conventions, build commands, test expectations, and local rules that should not be repeated in every task.
This guide focuses on the engineering decision behind AGENTS.md coding agents: what to standardize, what to constrain, and what evidence a reviewer should expect before accepting the result.
The core decision
Keep the root file short and operational. Explain where major components live, how to install dependencies, which commands are authoritative, and what the agent must not change. Add more specific files in subdirectories when a monorepo has distinct stacks or conventions.
A workflow that holds up in review
Test instructions from a clean checkout. Use commands that exit with meaningful status codes and avoid guidance that depends on a person’s workstation. Review the file when CI, package managers, or repository structure changes.
The failure mode to design around
AGENTS.md is guidance, not an authorization system. Do not put secrets in it or assume a statement can safely grant network or deployment access. Enforce permissions outside the model.
Implementation checklist
- Document structure and supported commands.
- Keep instructions scoped and current.
- Test them in a clean environment.
- Enforce permissions independently.
Turn the checklist into operating controls
- Document structure and supported commands: name the owner, the evidence that proves it happened, and the condition that should stop the run.
- Keep instructions scoped and current: name the owner, the evidence that proves it happened, and the condition that should stop the run.
- Test them in a clean environment: name the owner, the evidence that proves it happened, and the condition that should stop the run.
- Enforce permissions independently: name the owner, the evidence that proves it happened, and the condition that should stop the run.
The list becomes useful when every item produces visible evidence. Store that evidence with the task or pull request rather than in a private chat. A future reviewer should be able to tell which repository revision was used, which permission profile applied, what stopped or failed, and who accepted the remaining risk. For AGENTS.md coding agents, a short, complete record is more valuable than a long narrative that cannot be reproduced.
Move from one run to a repeatable practice
Pilot the workflow with engineers who will both dispatch and review tasks. Watch where they add missing context, where the agent asks for clarification, and where reviewers cannot reconstruct the intent. Turn repeated explanations into repository guidance or issue templates, but keep product decisions in the task itself. Review queue time as carefully as execution time. The workflow is healthy only when completed artifacts are reviewed promptly and rejected work improves the next task packet.
Before expanding the workflow, ask three review questions:
- What evidence shows that document structure and supported commands was satisfied, and would that evidence survive a rerun from the recorded commit?
- What evidence shows that keep instructions scoped and current was satisfied, and would that evidence survive a rerun from the recorded commit?
- What evidence shows that test them in a clean environment was satisfied, and would that evidence survive a rerun from the recorded commit?
Write the answers in the same place as the code review. That creates a compact decision record and lets the team compare later runs without relying on memory.
A practical acceptance test
Run the workflow from a clean checkout at a recorded commit. Give the agent only the documented task packet and the intended permission profile. Then ask a reviewer who did not launch the run to reproduce the important checks, explain the changed behavior, and identify the rollback path. The task passes only when the artifact, evidence, and repository state agree. Keep the failed examples as regression cases; they are more useful than a polished demo because they reveal where instructions, environment, permissions, or tests need improvement.
Related reading
- Agentic Coding in the Cloud: The Complete Guide
- How to Write Agent-Ready Engineering Issues
- Task Decomposition for Asynchronous Coding Agents
Primary references
Vendor features, limits, preview labels, and pricing can change. Recheck the linked first-party documentation for the current state before making a purchase or rollout decision.