# Deliver Acceptance Criteria

Generates structured Given/When/Then acceptance criteria for a user story or feature...

- Repository: https://github.com/product-on-purpose/pm-skills (780 stars)
- Category: Testing
- License: Apache-2.0
- Last updated: 2026-10-31
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add product-on-purpose/pm-skills --skill deliver-acceptance-criteria -g -a claude-code -y`
Codex: `npx skills add product-on-purpose/pm-skills --skill deliver-acceptance-criteria -g -a codex -y`
Cursor: `npx skills add product-on-purpose/pm-skills --skill deliver-acceptance-criteria -g -a cursor -y`
Gemini CLI: `npx skills add product-on-purpose/pm-skills --skill deliver-acceptance-criteria -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add product-on-purpose/pm-skills`

## Description

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.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 -->
# 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`
- 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

## 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.

2. **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.

The rest: https://github.com/product-on-purpose/pm-skills/blob/HEAD/skills/deliver-acceptance-criteria/SKILL.md