pull-request-feedback

pull-request-feedback is a skill for Claude Code from LandonSchropp/agent-toolkit. It costs 62 tokens per session (1,125 once invoked), scanned A, original, MIT.

A workflow for working through comments on a GitHub pull request, which is a proposed set of code changes awaiting review.

In plain words
What is it for?
It helps read review comments, update the code, reply or react to feedback, push changes, and request another review.
Why use it?
It gathers inline and general comments in order so feedback is not missed and changes can be discussed, made, and sent back for review.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the ls-git plugin — 8 skills, 1 hook shipped together

Good fit It helps read review comments, update the code, reply or react to feedback, push changes, and request another review.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/landonschropp/agent-toolkit/pull-request-feedback
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.

Any agent
npx skills add LandonSchropp/agent-toolkit --skill pull-request-feedback
Clone the repo
git clone --depth 1 https://github.com/LandonSchropp/agent-toolkit

Made for: Claude Code.

Or install ls-git, the plugin that ships this one along with the rest of its 8 skills, 1 hook.

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 pull-request-feedback

README.md
[![agentmods](https://agentmods.dev/badge/skills/landonschropp/agent-toolkit/pull-request-feedback/github.svg)](https://agentmods.dev/skills/landonschropp/agent-toolkit/pull-request-feedback)
Your own site
<a href="https://agentmods.dev/skills/landonschropp/agent-toolkit/pull-request-feedback"><img src="https://agentmods.dev/badge/skills/landonschropp/agent-toolkit/pull-request-feedback/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 pull-request-feedback

Your own site · 80×15
<a href="https://agentmods.dev/skills/landonschropp/agent-toolkit/pull-request-feedback"><img src="https://agentmods.dev/badge/skills/landonschropp/agent-toolkit/pull-request-feedback.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 62 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,125 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 $0.00062 $0.01125
Opus 5.5 $0.00025 $0.00450
Sonnet 5.5 $0.00012 $0.00225
Haiku 4.5 $0.00006 $0.00112

Measured 21d ago against content hash 6f8115b33456, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

pull-request-feedback 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 21d 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/ls-git/skills/pull-request-feedback/SKILL.md · 69 lines

How it starts

The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Pull Request Feedback

Context

Resolve the pull request and repository coordinates, and read the pull request's own title and description for context before looking at any feedback:

NUMBER=$(gh pr view --json number --jq '.number')
REPO=$(gh repo view --json owner,name --jq '"\(.owner.login)/\(.name)"')
gh pr view "$NUMBER" --json title,url,body

Collect the comments

Merge inline review comments and general conversation comments into one chronological list, sorted by created_at, tagging bot authorship:

gh api "repos/$REPO/pulls/$NUMBER/comments" --paginate --jq '[.[] | select(.in_reply_to_id == null) | {kind: "review", id, path, line, body, bot: (.user.type == "Bot"), url: .html_url, created_at}]'
gh api "repos/$REPO/issues/$NUMBER/comments" --paginate --jq '[.[] | {kind: "general", id, body, bot: (.user.type == "Bot"), url: .html_url, created_at}]'

Drop a bot: true comment only when it's purely informational — a status postback, linkback, or automated report with nothing to act on (a Linear linkback, a bundle-size report). Judge this from the body. Keep a bot comment that leaves substantive review feedback, such as an automated review tool flagging a real issue in the code — walk it like any other comment.

Summary

Before walking anything, print the review status and the comment count that survived the bot filter above:

gh pr view "$NUMBER" --json latestReviews --jq '.latestReviews[] | "\(.author.login): \(.state)"'

Format it like ✅ 2 approved · ❌ 1 changes requested · 💬 9 comments: ✅ per approving reviewer, ❌ per reviewer who requested changes, 💬 for the total comment count (inline plus general, after dropping informational bot comments).

Walk the comments

For each comment, in order:

  1. Print Comment <index> / <total>:, then the body as a blockquote, verbatim — no summarizing or paraphrasing.
  2. Discuss what to do about it and make any needed changes. Changes follow the normal commit-and-review flow already in effect for this session.
  3. Ask whether to reply, react, or move on:
    • Reply has any text in it (even alongside an emoji): post it as a reply, not a reaction.
      • Review comment: gh api "repos/$REPO/pulls/$NUMBER/comments/<id>/replies" -f body="..."
      • General comment: gh pr comment "$NUMBER" --body "..."
    • Reply is only an emoji: post it as a reaction. Map to GitHub's fixed reaction set: 👍 → +1, 👎 → -1, 😄/😆/😂 → laugh, 😕/😐 → confused, ❤️/😍 → heart, 🎉/🥳 → hooray, 🚀 → rocket, 👀 → eyes. If it doesn't map, say so and ask for a supported emoji or a text reply instead.
      • Review comment: gh api "repos/$REPO/pulls/comments/<id>/reactions" -f content="..."
      • General comment: gh api "repos/$REPO/issues/comments/<id>/reactions" -f content="..."
    • Move on: no action, continue to the next comment.

Read the full file on GitHub · 69 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. 21d ago First seen · 69 lines · 62 tokens per session scan A 6f8115b33456

Subscribe to this mod's changes

pull-request-feedback is a skill published in the GitHub repository LandonSchropp/agent-toolkit (3 stars, last pushed today), licensed MIT. It adds 62 tokens to every session and 1,125 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-25.

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