pr-review-loop

pr-review-loop is a skill for Claude Code, Codex from gabonio/agent-operator-toolkit. It costs 69 tokens per session (668 once invoked), scanned A, original, MIT.

A bounded process that repeatedly reviews current code changes or a pull request, fixes worthwhile issues, and verifies the result. A pull request is a proposed code change awaiting review before it is merged.

In plain words
What is it for?
Reviewing working-tree changes or pull requests, finding security and compatibility problems, applying justified fixes, running checks, and stopping when the changes are merge-ready.
Why use it?
It turns review feedback into a controlled review-and-fix cycle while protecting unrelated work. It also checks repository state and available verification before declaring changes ready.

Skill for Claude CodeCodex

Part of the builder-kit plugin — 5 skills shipped together

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.

agentmods
npx agentmods add skills/gabonio/agent-operator-toolkit/pr-review-loop
Any agent
npx skills add gabonio/agent-operator-toolkit --skill pr-review-loop
Clone the repo
git clone --depth 1 https://github.com/gabonio/agent-operator-toolkit

Made for: Claude Code, Codex.

Or install builder-kit, the plugin that ships this one along with the rest of its 5 skills.

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-loop

README.md
[![agentmods](https://agentmods.dev/badge/skills/gabonio/agent-operator-toolkit/pr-review-loop.svg)](https://agentmods.dev/skills/gabonio/agent-operator-toolkit/pr-review-loop)
Your own site
<a href="https://agentmods.dev/skills/gabonio/agent-operator-toolkit/pr-review-loop"><img src="https://agentmods.dev/badge/skills/gabonio/agent-operator-toolkit/pr-review-loop.svg" alt="Measured on agentmods" height="20"></a>
Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 668 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00069 $0.00668
Opus 5 $0.00034 $0.00334
Sonnet 5 $0.00014 $0.00134
Haiku 4.5 $0.00007 $0.00067

Measured 3d ago against content hash df8f5c487c12, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

pr-review-loop 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 3d 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/builder-kit/skills/pr-review-loop/SKILL.md · 24 lines

What it actually says

PR Review Loop

This loop runs locally with Builder Kit's adversarial reviewer. It requires no organization-specific review bot or slash command. Use repository instructions and the available Git/GitHub workflow.

  1. Identify the review target: the current working-tree and index changes, or the pull-request diff when a PR exists. Discover the base branch; never assume main or master.
  2. Record the starting head, diff boundary, repository status, checks available, and any pre-existing review comments. Protect unrelated changes throughout the loop.
  3. For a published PR, check base freshness before the first pass and before declaring it ready. Fetching, merging, pushing, posting GitHub comments, and resolving threads still require the authority normally required by the active environment.
  4. Start an iteration counter at one. Never exceed ten without a new user decision.
  5. Invoke the adversarial review against the complete current diff. Review behavior, security, data integrity, compatibility, operability, tests, and the approved objective—not just modified lines.
  6. Return only the three or four highest-value new findings in the iteration. Report fewer when fewer are real. Each finding must include severity, evidence, impact, a concrete fix or validation, and the tightest useful path:line anchor.
  7. Present findings as review comments. When the active interface supports inline comments, attach them to the anchored lines. Publish them to GitHub only when the user requested remote review activity; otherwise keep the comments in the task.
  8. Verify each finding against code, tests, specifications, and local rules. Classify it as fix, false positive, duplicate, accepted risk, or user decision.
  9. Fix the current batch when changes are authorized. Keep fixes scoped, add focused tests for behavior changes, and run proportionate verification. Do not commit, push, or resolve remote conversations unless that action is authorized.
  10. Mark local comments addressed only after the fix is verified. For remote threads, reply with the disposition and verification evidence; include a fixing commit link when one has been pushed, then resolve only fully addressed threads.
  11. Recompute the complete diff and run a fresh adversarial pass. Do not restrict later passes to the previous batch's files; fixes can expose or introduce other problems.
  12. If no actionable findings remain, run the repository's merge-readiness checks and recheck base freshness and unresolved conversations when a PR exists.

Stop with ready only when there are no actionable findings, required checks pass, no unresolved blocking conversations remain, and the reviewed head contains the required base. Stop earlier with ready with accepted risks, blocked on decision, or iteration limit reached when appropriate. Report the boundary, iterations, findings fixed/declined/open, verification, commits or remote comments actually made, base state, and final verdict.

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 3d ago First seen · 24 lines · 69 tokens per session scan A df8f5c487c12

Subscribe to this mod's changes

pr-review-loop is a skill published in the GitHub repository gabonio/agent-operator-toolkit (1 stars, last pushed 1mo ago), licensed MIT. It adds 69 tokens to every session and 668 once invoked, about $0.0003 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 2026-08-31.

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