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AI agent for authors

Beta Reader Feedback Pattern Agent

A ranked revision plan built from beta feedback, checked after each revision round

AnalysisDecisionsPlanningWritersCreatives
See how it worksGet access
Beta Reader Feedback Pattern Agent: what goes in, what the agent does and what you get

What it does

Beta readers disagree, and an author facing fifty comments cannot easily see which notes matter. This agent collects the feedback by chapter and reader and clusters repeated issues, such as pacing in chapter 6 or a confusing character name. It checks whether agreement comes from the right readers, for example fans of the genre versus casual readers, and flags outliers. It ranks revision priorities by how many readers raised an issue and how much it affects the story. After the author revises, it reruns the process on new feedback to see whether the issue is gone. The author approves the plan. Edge case: one reader loved the ending that three others disliked, so the agent labels it as split rather than dropping either view.

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, continueApprovedYes, continueNoNo 1 STARTS WHEN Beta feedback round arrives 2 USES A TOOL Read all comments with chapter and reader 3 DOES Cluster comments into issues 4 DOES Count readers per issue and weigh by reader type 5 CHECKS THE RESULT Does each cluster have a clear single issue and asupporting quote? If not: split or merge clusters and recount. Back tostep 3. 6 DOES Rank issues by readers and story impact, labelingsplit opinions and outliers 7 DOES Draft the revision plan 8 YOU APPROVE Author approves the plan 9 USES A TOOL Read feedback on the revised draft 10 CHECKS THE RESULT Are the top issues gone or reduced in the newfeedback? If not: reopen the issue and propose another fix. Backto step 4. 11 RESULT Revision plan and issue tracker
Read the steps as a list
  1. Beta feedback round arrives
  2. Read all comments with chapter and reader
  3. Cluster comments into issues
  4. Count readers per issue and weigh by reader type
  5. Does each cluster have a clear single issue and a supporting quote?If not: split or merge clusters and recount. Back to step 3.
  6. Rank issues by readers and story impact, labeling split opinions and outliers
  7. Draft the revision plan
  8. Author approves the planThe agent waits here for your OK.
  9. Read feedback on the revised draft
  10. Are the top issues gone or reduced in the new feedback?If not: reopen the issue and propose another fix. Back to step 4.
  11. Revision plan and issue tracker

How it decides

Issues are clustered by meaning. Priority rises with the number of readers and with readers who match the target audience.

  • Treat an issue as major when 3 or more readers raise it
  • Weigh target audience readers more heavily
  • Label split opinions instead of dropping them
  • Quote readers exactly in the notes

Make it yours

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

  • Major issue count (default 3 readers)
  • Reader types to weigh
  • Chapters included
  • Plan format

What keeps you in control

It always asks you first

  • Revision plan

Hard limits

  • Never rewrites the manuscript
  • Never shares reader comments outside the author's team

It stops when

  • Done: top issues resolved or accepted
  • Stop: fewer than 3 readers responded

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 happensTwelve beta readers gave 140 comments. The agent clustered them into 9 issues. Seven readers said chapter 6 dragged, five found the villain's motive unclear and three disliked the ending, while two loved it. The first clustering lumped pacing and length, so the cluster check failed and it split them. After the rewrite, new readers raised chapter 6 only once. The author approved the plan.

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