deliver-acceptance-criteria

1<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 -->
2# Acceptance Criteria
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4Acceptance criteria define the observable behavior that must be true for a story or feature to be considered done. This skill turns feature context into concise, testable Given/When/Then scenarios that engineers and QA can verify without guessing intent.
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6## When to Use
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8- After a user story, PRD section, or feature slice is defined
9- When a team needs clear pass/fail conditions for implementation
10- When writing QA-ready criteria for sprint planning or handoff
11- When a story has edge cases, error paths, or non-functional expectations that should be explicit
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13## When NOT to Use
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15- You need the user stories themselves -> use `deliver-user-stories`; this skill deepens a story that already exists
16- You need systematic failure coverage across a whole feature -> use `deliver-edge-cases`; this skill stays story-scoped
17- There is no story or slice to bind criteria to yet -> use `deliver-prd` or `deliver-user-stories` first
18- You are defining success metrics for an experiment, not done-ness for a story -> use `measure-experiment-design`
19- The criterion is a rate over model output, such as "90% of answers are faithful to their sources" -> use the AI Behavior and Evaluation section of `deliver-prd`, which says a rate needs a designed sample to verify it, and what to record until one exists
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21## Instructions
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23When asked to create acceptance criteria, follow these steps:
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