What are acceptance criteria?
Acceptance criteria are observable, testable conditions that a feature or story must satisfy before it is accepted.
Glossary
Acceptance criteria define observable conditions a story must satisfy before generated code can be accepted after review.
Why it matters
Acceptance criteria tell an AI coding agent what done means and tell the developer what to inspect before accepting the output.
Acceptance criteria are observable conditions a story must satisfy before generated code can be accepted. For AI coding, they give the agent a definition of done and give the developer a checklist for reviewing behavior, edge cases, constraints, and unresolved work.
Acceptance criteria are specific conditions a story must meet to be considered complete. They should be observable, testable, and tied to product behavior.
Acceptance criteria help prevent vague prompts from turning into vague diffs. They give the implementation engine a target and give the reviewer a checklist.
Good acceptance criteria name the user-facing behavior, relevant edge cases, constraints, and non-goals. They avoid broad statements like “works well” or “make it better.”
Hal’s PRD-driven workflow encourages requirements and stories that can be validated before implementation. If acceptance criteria are unclear, split or rewrite the story before running the loop.
Short answers before you put this into an agent workflow.
Acceptance criteria are observable, testable conditions that a feature or story must satisfy before it is accepted.
They reduce ambiguity and make generated changes easier to validate against the original requirement.
Keep exploring the pieces of a reviewable coding loop.