Technical

Generate user stories with acceptance criteria

AI writes 15 complete user stories with testable acceptance criteria from your feature description.

Free AI Tool4 min read
Describe the feature you want user stories for... Example: Building a search feature for our e-commerce site. Users should be able to search products by name, filter by category and price, sort results, and save searches for later.
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Generate user stories with acceptance criteria

River's User Stories Generator creates 15 complete agile user stories with detailed acceptance criteria from your feature description. You provide the feature concept, and the AI writes stories from user perspective with clear acceptance criteria, priority levels, and story point estimates. Whether you're planning sprints, defining requirements, or aligning teams on functionality, you get professional user stories that drive development and testing.

Unlike vague requirements, we create testable specifications. The AI understands agile story conventions (user perspective, clear value proposition, testable criteria, appropriate granularity), breaks features into implementable pieces, and writes criteria QA can verify. You get stories that answer what to build and how to know it's done.

This tool is perfect for product managers planning features, scrum masters preparing backlogs, QA teams creating test cases, and teams practicing agile development. If you need to break features into stories, or if you want to improve story quality and testability, this tool helps. Use it during planning to create clear, actionable stories that guide development and testing.

What Makes User Stories Effective

User stories succeed when they provide just enough detail for implementation without overspecifying. Effective stories follow (As a [persona], I want [action] so that [benefit]) format, focus on user value (not technical implementation), include clear acceptance criteria (testable conditions), are appropriately sized (completable in one sprint), have priority levels, and specify story points or effort estimates. Weak stories are too large, too vague, or focus on implementation rather than user needs. Strong stories enable teams to understand what users need and build incrementally toward that goal.

The best user stories follow INVEST principles: Independent (can be developed separately), Negotiable (details can evolve), Valuable (delivers user value), Estimable (team can estimate effort), Small (fits in sprint), Testable (has clear success criteria). Acceptance criteria should be specific (no vague terms), testable (verifiable as pass/fail), complete (covers happy path and edge cases), and focused on behavior (what system does, not how it's built). Good criteria help developers know what to build and QA know what to test. They prevent scope creep by defining done clearly.

To improve user stories, write from actual user perspective (not internal team perspective). Focus on why (the benefit), not just what (the action). Break large stories (epics) into smaller stories. Make acceptance criteria specific enough to test but flexible enough to allow implementation choices. Include both happy path and error cases. Prioritize ruthlessly (everything can't be must-have). Estimate effort realistically. Review stories with whole team (developers, QA, designers) before sprint. Refine continuously based on learning. Remember: stories are conversation starters, not complete specifications. Details emerge through discussion. Good stories enable teams to build iteratively with clear understanding of success.

What You Get

15 complete user stories for your feature

Detailed acceptance criteria for each story

Priority levels (must-have, should-have, nice-to-have)

Story point estimates and dependencies

Organized by epic or feature area

Ready for backlog or sprint planning

How It Works

  1. 1
    Describe your featureProvide feature concept and user needs
  2. 2
    AI generates 15 user storiesOur AI creates complete stories with acceptance criteria in 3 to 5 minutes
  3. 3
    Review and refineRead through stories, adjust priorities, add details
  4. 4
    Add to backlog and planImport to Jira, prioritize, assign to sprints

Frequently Asked Questions

How many stories should a feature have?

Depends on feature size. This tool generates 15 stories as starting point. Simple features might need fewer. Complex features might need more. Use generated stories as foundation. Combine similar stories, split large ones, or add missing stories based on your needs. 15 provides good coverage for typical feature.

What makes good acceptance criteria?

Specific, testable, complete. Good: (User can filter products by selecting category from dropdown. Results update immediately. No results message shown if category empty.). Bad: (Filtering should work.). Criteria should be verifiable as pass/fail. QA should be able to write test cases directly from criteria.

Should technical stories be written as user stories?

Technical stories (refactoring, infrastructure) can use modified format: (As a [team], I want [technical work] so that [business value]). Example: (As the dev team, I want to refactor authentication module so that we can add SSO support faster.). Focus on business value even for technical work.

How do I estimate story points?

Story points are relative effort estimation. Common scale: 1 (simple), 2, 3 (medium), 5 (complex), 8 (very complex). Stories over 8 should be broken down. Team estimates together using planning poker or similar. Generated estimates are starting points. Your team's velocity and experience determine actual estimates.

Should every story be independent?

Ideally yes, but dependencies happen. Document dependencies clearly (blocks, blocked by). Try to minimize dependencies by ordering stories well. Sometimes technical foundation story must complete before feature stories. That's okay. Just make dependencies explicit so planning accounts for them.

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