pr-feedback-collector

pr-feedback-collector is an agent for Claude Code from rp1-run/rp1. It costs 35 tokens per session (1,767 once invoked), scanned A, original, Apache-2.0.

A pull-request feedback collector that gathers review comments and turns them into organized task lists. Review comments are notes from people or tools about proposed code changes.

In plain words
What is it for?
It collects comments from GitHub, classifies their priority and type, extracts actionable tasks, and writes structured feedback documents without implementing the changes.
Why use it?
Feedback spread across a pull request is easy to miss or lose. Organizing it preserves context and makes follow-up work easier to track.

Agent for Claude Code

Written for Claude Code: arguments in frontmatter. Also seen: model in frontmatter; positional $N argument.

Part of the rp1-dev plugin — 23 skills, 36 agents shipped together

Good fit It collects comments from GitHub, classifies their priority and type, extracts actionable tasks, and writes structured feedback documents without implementing the changes.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/rp1-run/rp1/pr-feedback-collector
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo
git clone --depth 1 https://github.com/rp1-run/rp1

Made for: Claude Code.

Or install rp1-dev, the plugin that ships this one along with the rest of its 23 skills, 36 agents.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for pr-feedback-collector

README.md
[![agentmods](https://agentmods.dev/badge/agents/rp1-run/rp1/pr-feedback-collector/github.svg)](https://agentmods.dev/agents/rp1-run/rp1/pr-feedback-collector)
Your own site
<a href="https://agentmods.dev/agents/rp1-run/rp1/pr-feedback-collector"><img src="https://agentmods.dev/badge/agents/rp1-run/rp1/pr-feedback-collector/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for pr-feedback-collector

Your own site · 80×15
<a href="https://agentmods.dev/agents/rp1-run/rp1/pr-feedback-collector"><img src="https://agentmods.dev/badge/agents/rp1-run/rp1/pr-feedback-collector.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 35 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,767 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00035 $0.01767
Opus 5 $0.00017 $0.00883
Sonnet 5 $0.00007 $0.00353
Haiku 4.5 $0.00003 $0.00177

Measured 2d ago against content hash 2e994a28783e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

pr-feedback-collector scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/dev/agents/pr-feedback-collector.md · 184 lines

How it starts

The opening of the file, as written. The whole thing — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PR Feedback Collector - Review Comments to Actionable Tasks

You are PRCollectGPT, an expert tool for collecting and organizing pull request review comments into structured, actionable task lists. Your role is to gather PR feedback, classify it systematically, and create organized documents that developers can use to address comments efficiently.

IMPORTANT: You collect and organize feedback - you do not implement changes. Your job is to preserve all context, extract actionable tasks, and create clear documentation for systematic resolution.

<feature_id>$1</feature_id> <pr_number>$2</pr_number> <branch_name>$3</branch_name> <include_resolved>$4</include_resolved> <group_by>$5</group_by> <work_root>{{WORK_ROOT from prompt}}</work_root>

Your Task

Systematically collect all PR review comments and organize them into a comprehensive feedback document. Follow this process:

Before proceeding with collection, work through your collection strategy in <collection_planning> tags inside your thinking block:

  1. Validate each configuration parameter - list each parameter, its provided value (or note if using default), and any validation requirements
  2. Plan your GitHub CLI commands - list the specific gh commands you'll need to execute for PR detection, metadata collection, and comment retrieval
  3. Map out your comment classification approach - for each priority level (Blocking, Important, Suggestion, Style), list the specific keywords you'll look for and explain your decision logic
  4. Plan your error handling - identify potential failure points (auth issues, missing PR, API limits, etc.) and your response strategy
  5. Design your file organization approach - explain how you'll group comments and structure the output based on the GROUP_BY parameter
  6. Outline your task extraction methodology - describe how you'll identify actionable tasks from comment text using the specified patterns

It's OK for this section to be quite long.

Then execute the following workflow:

Read the full file on GitHub · 184 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 184 lines · 35 tokens per session scan A 2e994a28783e

Subscribe to this mod's changes

pr-feedback-collector is an agent published in the GitHub repository rp1-run/rp1 (38 stars, last pushed 2d ago), licensed Apache-2.0. It adds 35 tokens to every session and 1,767 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-07.

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