Desired change
“Add email verification”
AI Ready
Explicit repository context helps coding agents understand architecture and constraints before implementing a change.
Repository workflow
The useful part of AI readiness is concrete: give the agent the same repository rules a developer needs.
Desired change
“Add email verification”
mainAGENTS.mdCommands, scope, constraints, and verification expectations.
ARCHITECTURE.mdResponsibilities, dependencies, and important design decisions.
AI_RULES.mdPredictable coding rules and repository boundaries.
AGENT_CONTRIBUTING.mdA focused contribution and review workflow.
Benefits
Repository context turns an open-ended request into a bounded, reviewable change.
Add email verificationLocate responsibilities, commands, and project decisions.
Work out which rules and constraints apply to the change.
Determine how the repository expects behavior to be checked.
Structure, commands, and decisions are directly discoverable.
Constraints and verification requirements stay visible.
Developers and coding agents follow the same boundaries.
context → constraints → verificationQuestions
An AI-ready repository makes architecture, constraints, commands, contribution rules, and verification expectations explicit so coding agents can work with the same boundaries as developers.
AGENTS.md gives coding agents repository-specific instructions, including important commands, scope boundaries, conventions, and expected verification.
No. Context improves focus and consistency, but generated changes still need the same testing, security review, and human judgment as other changes.
Choose your foundation
Start with one documented capability, review its boundary, and build the application-specific behavior on top.