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SKILL verified Apache-2.0 Self-run

Deliver Acceptance Criteria

skill-product-on-purpose-pm-skills-deliver-acceptance-criteria · by product-on-purpose

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-e…

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Install

$ agentstack add skill-product-on-purpose-pm-skills-deliver-acceptance-criteria

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Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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Reliability & compatibility

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Declared compatibility

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Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

Acceptance Criteria

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.

When to Use

  • After a user story, PRD section, or feature slice is defined
  • When a team needs clear pass/fail conditions for implementation
  • When writing QA-ready criteria for sprint planning or handoff
  • When a story has edge cases, error paths, or non-functional expectations that should be explicit

When NOT to Use

  • You need the user stories themselves -> use deliver-user-stories; this skill deepens a story that already exists
  • You need systematic failure coverage across a whole feature -> use deliver-edge-cases; this skill stays story-scoped
  • There is no story or slice to bind criteria to yet -> use deliver-prd or deliver-user-stories first
  • You are defining success metrics for an experiment, not done-ness for a story -> use measure-experiment-design

Instructions

When asked to create acceptance criteria, follow these steps:

  1. Confirm the story or feature scope

Identify the exact slice of work. If the scope is unclear, ask for the user story, PRD section, or feature description before drafting criteria.

  1. Separate the happy path from exceptions

Start with the primary success flow, then add edge cases and error states that are likely or costly if missed.

  1. Write each criterion as an observable scenario

Use Given/When/Then language only. Keep each criterion independently testable and avoid implementation details.

  1. Cover recovery and failure behavior

Describe what the user sees or can do when validation fails, a dependency is unavailable, or a save action cannot complete.

  1. Include non-functional expectations

Add criteria for performance, accessibility, security, reliability, or auditability when they matter to the story.

  1. Avoid duplication and overlap

Each criterion should test one outcome. If two criteria describe the same behavior, merge or split them until the intent is clear.

  1. Review for testability

Ensure a reviewer can pass or fail each criterion without interpretation. If a statement is subjective, rewrite it into a measurable outcome.

Output Contract

Use references/TEMPLATE.md as the output format. A complete response should:

  • Restate the feature or story context
  • Group criteria into happy path, edge cases, error states, and non-functional criteria
  • Use explicit Given/When/Then statements for each criterion
  • Note assumptions or open questions when context is incomplete

Quality Checklist

Before finalizing, verify:

  • [ ] The criteria map to a specific story or feature slice
  • [ ] The happy path is covered first
  • [ ] Edge cases are explicit, not implied
  • [ ] Error states include user-visible recovery behavior
  • [ ] Non-functional criteria are included when relevant
  • [ ] Each criterion is testable and has one clear outcome
  • [ ] No implementation details leak into the acceptance criteria

Examples

See references/EXAMPLE.md for a completed example based on a realistic e-commerce checkout flow.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.