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New issue intake sorter

Reads each new issue on your repo and sorts it as ready to work, needs more info, or too big. You get a clean queue and reporters get asked for missing details.

EngineeringWorks with Claude Code · OpenAI Agents SDK+1Community example
Build your promptSee requirements

What it does

  • Reads each new or reopened issue and its comments
  • Labels it ready, needs info, or needs splitting
  • Drafts a question for the reporter when details are missing
  • Rechecks waiting issues on weekday mornings

Your approval boundaries

Approval required

These actions always wait for your yes:

  • Closing any issue
  • Posting comments in public
  • Merging any pull request

You decide what happens next.

More about this workflow

This setup is for developers and small engineering teams who want fewer chores. It takes a repeat chore off your plate and hands back something you can check quickly.

First, it reads each new or reopened issue and its comments. Next, it labels it ready, needs info, or needs splitting. Then it drafts a question for the reporter when details are missing. Finally, it rechecks waiting issues on weekday mornings. It works with your git host and CI, each on its own login with limited access.

You get the prep work done and waiting for you. The agent stops and asks for your yes before closing any issue, posting comments in public and merging any pull request, and says plainly if a step cannot be undone.

“a human approval is needed regardless of what bots do”
bbertucc bbertucc on GitHub · May 28, 2026
Before you startGit host · CI accessScoped permissionsClaude Code or OpenAI Agents SDK
Explore required tools and model recommendations

Tools and access

  • GitHub

    Handles the git host and ci part of this job. Grant a fine-grained token, read code and write comments.

    API required: Yes. Needs a GitHub App or a fine-grained personal access token scoped to the repos it needs.

    Sign up: Create a GitHub account

Official links only. Not sponsored, no affiliate links.

Model recommendations

Best pick

Claude Opus 5.5

Its maker points to it for long running coding work.

$4 per million input tokens, $20 per million output tokens.

Anthropic docs as of October 11, 2026

Cheaper backup

Claude Sonnet 5.5

Half the price per token and still strong for reviews and docs.

$2 per million input tokens, $10 per million output tokens.

Anthropic docs as of October 11, 2026

Our own picks. Not sponsored, no affiliate links.

Build your prompt

Add your details, then copy the prompt into your tool.

1Your details

Fill these in and the prompt updates as you type.

e.g. ready, needs info

2Your prompt

4 of 4 still empty
Fill these in before you run it: [YOUR REPO] [YOUR LABELS: e.g. ready, needs info] [WHAT COUNTS AS READY TO WORK] [AREAS IT SHOULD NEVER TOUCH] You are the New issue intake sorter agent. Reads each new issue on your repo and sorts it as ready to work, needs more info, or too big. You get a clean queue and reporters get asked for missing details. Use only the details filled in above. If any [BRACKETED] item is still blank or unclear, stop and ask for it first. Do not guess. What you do on your own: - Reads each new or reopened issue and its comments - Labels it ready, needs info, or needs splitting - Drafts a question for the reporter when details are missing - Rechecks waiting issues on weekday mornings What you must never do without a yes from a person: - Closing any issue - Posting comments in public - Merging any pull request Rules: - Before any step on the list above, stop and ask. Say in plain words what you want to do, who it affects, and whether it can be undone. - If something cannot be undone, say so first, in one short line. - Write drafts, not final actions. A person sends, pays, posts, or deletes. - Keep a short log of every action you took and every source you read. - If you are unsure, ask instead of guessing.
View run instructionsPaste into: Claude Code, OpenAI Agents SDK, n8n

Your answers stay in this browser only.

Run your workflow

Connect your tools with only the access this setup needs, then follow these steps.

Steps

Do these in order. Test on old data before it touches live work.

  1. 1Connect GitHub with its own login, not yours. Grant a fine-grained token, read code and write comments.
  2. 2Paste the prompt where your harness takes instructions. See the note under the Copy button.
  3. 3Do a dry run on old or test data first. Check every draft and every stop point by hand before you let it near live work.
  4. 4Read its log after the first real run. Only widen access once a week of runs looks clean.

Safeguards and trust score

The score describes this example setup’s access, approval boundaries, ability to undo changes, and scope.

Access18 / 30

Can draft things that send or spend, so it sits close to risky actions.

Human approval30 / 30

Waits for a yes on: closing any issue, posting comments in public, merging any pull request.

Undo and logs14 / 20

Proposes changes to live records, so the setup needs a change log and a way back.

Scope18 / 20

Runs on its own login across 2 tools. Fewer connections means a smaller blast radius.

How to raise it

  • Access: Take away its ability to send, post or spend. Let it only write drafts, and have a person press send or pay from their own account +6
  • Undo and logs: Stop it from editing live records. Have it write the change as a proposal you apply, and keep a log of every change with a way to roll it back +3
  • Scope: Run it on one tool only, with its own login that can see just what this job needs +2

Do all of these to reach 91, up from 80.

Want help getting there? Get an AI Trust Audit from Pixeldesigns

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