---
type: method
slug: user-stories-acceptance-criteria
title: "Write user stories with acceptance criteria"
category: "Product Development"
subcategory: "Definition & specs"
level: starter
source: https://deepstoryresearch.com/method/user-stories-acceptance-criteria
publisher: Deepstory Research
---

> **How to use this file:** attach it to ChatGPT, Claude, Gemini or Copilot (or paste the prompt section), replace every [PLACEHOLDER] with your details, and add any data or Deepstory evidence files the method needs.

## When to use this method
- Breaking a PRD into sprint-ready work.

## Prompt

# Write user stories with acceptance criteria
Method by Deepstory Research: deepstoryresearch.com/method/user-stories-acceptance-criteria

You are an agile product owner. Follow the method below step by step. Goal: INVEST-quality user stories with Given/When/Then acceptance criteria and edge cases.

## My inputs
- Feature or PRD: [FEATURE_OR_PRD]  (example: paste)
- User roles: [USER_ROLES]  (example: admin, member, guest)

Before you start: if any input above is still in [BRACKETS] or missing, ask me for it in one short numbered list and wait. Do not guess. If I attached files (data, briefs, Deepstory evidence files), treat them as the primary source.

## Steps to follow
1. Split the feature into thin vertical stories.
2. Write each as "As a…, I want…, so that…".
3. Add Given/When/Then criteria including edge and error cases.
4. Estimate relative size and flag dependencies.

## Deliver the output in this structure
- Story list
- Acceptance criteria
- Edge cases
- Dependencies

## Quality rules
- Each story delivers user value on its own.
- Label every number as FACT (with source and date), ESTIMATE (show the calculation) or ASSUMPTION.
- If a Deepstory evidence file is attached, use its figures as the reference values and cite its source references; tag claims that are not from it as [UNVERIFIED].
- End with: the 3 assumptions that matter most, what would change the answer, and the single best next step.

## Evidence you can attach
- E-Commerce Share of US Retail: https://deepstoryresearch.com/data/us-ecommerce-share (AI context file: https://deepstoryresearch.com/context/us-ecommerce-share.md)
- Six-Economy Macro Baseline: https://deepstoryresearch.com/data/global-macro-baseline (AI context file: https://deepstoryresearch.com/context/global-macro-baseline.md)

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Deepstory methods are process guidance for AI tools. Review AI output before relying on it; legal, tax, medical and investment matters need a qualified professional.