Generates structured Given/When/Then acceptance criteria for a user story or feature slice, covering the happy path, key failure scenarios, and non-functional expectations in testable form. Use when turning requirements into verifiable scenarios for engineering handoff and QA sign-off. For a dedicated catalog of boundary conditions, error states, and recovery paths across a feature, use deliver-edge-cases; to write the stories themselves, use deliver-user-stories.
npx skills add https://github.com/product-on-purpose/pm-skills --skill deliver-acceptance-criteria
<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 -->
Acceptance 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.
deliver-user-stories; this skill deepens a story that already existsdeliver-edge-cases; this skill stays story-scopeddeliver-prd or deliver-user-stories firstmeasure-experiment-designWhen asked to create acceptance criteria, follow these steps:
Identify the exact slice of work. If the scope is unclear, ask for the user story, PRD section, or feature description before drafting criteria.
Start with the primary success flow, then add edge cases and error states that are likely or costly if missed.
Use Given/When/Then language only. Keep each criterion independently testable and avoid implementation details.
Describe what the user sees or can do when validation fails, a dependency is unavailable, or a save action cannot complete.
Add criteria for performance, accessibility, security, reliability, or auditability when they matter to the story.
Each criterion should test one outcome. If two criteria describe the same behavior, merge or split them until the intent is clear.
Ensure a reviewer can pass or fail each criterion without interpretation. If a statement is subjective, rewrite it into a measurable outcome.
Use references/TEMPLATE.md as the output format. A complete response should:
Before finalizing, verify:
See references/EXAMPLE.md for a completed example based on a realistic e-commerce checkout flow.
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Use when working with error debugging multi agent review
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This skill should be used when the user asks to "evaluate agent performance", "build test framework", "measure agent quality", "create evaluation rubrics", or mentions LLM-as-judge, multi-dimensional evaluation, agent testing, or quality gates for agent pipelines.
Take product-on-purpose/deliver-acceptance-criteria from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.