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AI agent for product owners

User Story Refinement Agent

Backlog items that are clear, testable and ready before the team picks them up

User Story Refinement Agent: what goes in, what the agent does and what you get

What it does

When stories are unclear, the team builds the wrong thing or stops mid-sprint to ask questions. Before each refinement session, this agent pulls the queued stories, linked designs and the team's definition of ready. It checks each story for a clear user and value, testable acceptance criteria, named dependencies and a size that fits one sprint. It drafts missing acceptance criteria from the story's intent and lists vague phrases as questions for the product owner. When a story is too large, it proposes a split into smaller stories that each deliver value. It then checks that every blocking dependency has an owner, and if one is missing it adds a question and checks again. It never marks a story ready on its own; the product owner approves each refined story. Edge case: a story that hides two different user needs is flagged for splitting by need, not just by size.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueYes, continueApprovedNoNo 1 STARTS WHEN Stories queued for the next refinement session 2 USES A TOOL Pull the queued stories, linked designs and theteam's definition of ready 3 DOES Check each story against the definition of ready 4 DOES Draft missing acceptance criteria and list ambiguousphrases 5 CHECKS THE RESULT Is each story clear, testable and sized for onesprint? If not: raise questions for the stakeholder or propose asplit, then re-check. Back to step 3. 6 DOES Check dependencies on other teams and open questions 7 CHECKS THE RESULT Are all blocking dependencies named with an owner? If not: draft a dependency note and ask the owning teamfor a date. Back to step 6. 8 YOU APPROVE Product owner approves the refined stories 9 RESULT Ready stories for sprint planning
Read the steps as a list
  1. Stories queued for the next refinement session
  2. Pull the queued stories, linked designs and the team's definition of ready
  3. Check each story against the definition of ready
  4. Draft missing acceptance criteria and list ambiguous phrases
  5. Is each story clear, testable and sized for one sprint?If not: raise questions for the stakeholder or propose a split, then re-check. Back to step 3.
  6. Check dependencies on other teams and open questions
  7. Are all blocking dependencies named with an owner?If not: draft a dependency note and ask the owning team for a date. Back to step 6.
  8. Product owner approves the refined storiesThe agent waits here for your OK.
  9. Ready stories for sprint planning

How it decides

It measures each story against the definition of ready and proposes a split when a story is too large or mixes separate needs.

  • Require testable acceptance criteria
  • Split stories too big for one sprint
  • Split stories that mix separate user needs

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Definition of ready
  • Acceptance criteria style
  • Sprint size limit
  • Split rules

What keeps you in control

It always asks you first

  • Marking stories ready

Hard limits

  • Does not mark stories ready without approval
  • Does not invent requirements beyond intent

It stops when

  • Done: stories meet the definition of ready
  • Stop: the product goal is unclear

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensOn March 4, nine stories were queued for the Thursday refinement session. Story 214, improve search, failed the ready check: no acceptance criteria and it mixed filtering with sorting. The agent proposed two stories and drafted five criteria for each. It also flagged the phrase fast results and suggested under two seconds for 10,000 items. On the re-check both stories fit one sprint. The product owner approved seven stories and sent two back.

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