pr-review-sweep

pr-review-sweep is a skill for Claude Code from Generous-Corp/pulp. It costs 73 tokens per session (1,259 once invoked), scanned A, original, MIT.

A pull-request review checklist and workflow that gathers automated and human comments and helps address them. A pull request is a proposed code change awaiting review before it is merged.

In plain words
What is it for?
Use it to sweep review comments on substantial or risky pull requests, check feedback from bots and people, and handle findings involving concurrency, state changes, serialization, or destructive actions.
Why use it?
A passing build does not mean reviewers have finished, because comments may arrive later or after merging. This helps catch serious logic and safety problems before they ship.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: installed under .agents/ (shared by several agents); mentions Codex.

Part of the pulp plugin — 64 skills, 30 commands, 3 hooks, 1 MCP server shipped together

Good fit Use it to sweep review comments on substantial or risky pull requests, check feedback from bots and people, and handle findings involving concurrency, state changes, serialization, or destructive actions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/generous-corp/pulp/pr-review-sweep
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 Generous-Corp/pulp --skill pr-review-sweep
Clone the repo
git clone --depth 1 https://github.com/Generous-Corp/pulp

Made for: Claude Code.

Or install pulp, the plugin that ships this one along with the rest of its 64 skills, 30 commands, 3 hooks, 1 MCP server.

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-review-sweep

README.md
[![agentmods](https://agentmods.dev/badge/skills/generous-corp/pulp/pr-review-sweep.svg)](https://agentmods.dev/skills/generous-corp/pulp/pr-review-sweep)
Your own site
<a href="https://agentmods.dev/skills/generous-corp/pulp/pr-review-sweep"><img src="https://agentmods.dev/badge/skills/generous-corp/pulp/pr-review-sweep.svg" alt="Measured on agentmods" height="20"></a>
Per session 73 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,259 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00073 $0.01259
Opus 5 $0.00036 $0.00629
Sonnet 5 $0.00015 $0.00252
Haiku 4.5 $0.00007 $0.00126

Measured 2d ago against content hash d4c7548215b0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

pr-review-sweep 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.

.agents/skills/pr-review-sweep/SKILL.md · 107 lines

How it starts

The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PR Review Sweep

Automated reviewers (cubic-dev-ai, chatgpt-codex-connector / Codex) and humans leave findings on PRs asynchronously — often seconds to minutes after the PR opens, and sometimes only after it merges. A PR that built green is not a reviewed PR. This skill makes the sweep a deliberate step so real P1s (races, state-clobbers, unguarded destructive paths) don't slip through on the exact kind of change where they hurt most.

The rule that motivated this skill: a self-identified P1 on a destructive path was shipped as a "follow-up" and the reviewers confirmed it (plus three more) after merge. Cheap to catch at sweep time; a roundtrip to catch later.

When to sweep (and when not to)

Always sweep — material PRs:

  • Touches shipped source / logic: core/**, examples/**, ship/**, tools/cli/**, src/** (Shipyard), CMake/build wiring.
  • Concurrency, lock ordering, state machines, serialization, RT-audio, or any destructive / mutating path (delete, abandon, overwrite, force). Treat these as high-risk regardless of diff size.
  • Large diffs, or a stack of commits — more surface, more asynchronous review.

Skip is fine — non-material PRs:

  • Docs-only / comment-only / pure rename / formatting.
  • Trivial config or version-bump-only changes.

If unsure, sweep. It costs one API read and a few minutes of triage.

The sweep

Use ghapp for GitHub API reads (its own rate-limit bucket; plain gh burns the shared personal token). Use gh for creating/merging PRs.

Pull all three comment surfaces — findings land in different places:

REPO=danielraffel/<repo>; N=<pr>
# Inline review comments (code-anchored — where the bots put P1/P2 findings)
ghapp api repos/$REPO/pulls/$N/comments \
  --jq '.[] | "--- \(.path):\(.line // .original_line) by \(.user.login)\n\(.body)\n"'
# PR-level reviews (approve/request-changes summaries)
ghapp api repos/$REPO/pulls/$N/reviews \
  --jq '.[] | "\(.user.login) [\(.state)]: \(.body)"'
# Issue comments (human notes, "potential issues flagged here")
ghapp api repos/$REPO/issues/$N/comments \
  --jq '.[] | "--- by \(.user.login)\n\(.body)\n"'

Read the full file on GitHub · 107 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 · 107 lines · 73 tokens per session scan A d4c7548215b0

Subscribe to this mod's changes

pr-review-sweep is a skill published in the GitHub repository Generous-Corp/pulp (16 stars, last pushed today), licensed MIT. It adds 73 tokens to every session and 1,259 once invoked, about $0.0004 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 2026-09-04.

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