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.
npx agentmods add skills/gabonio/agent-operator-toolkit/pr-review-loopnpx skills add gabonio/agent-operator-toolkit --skill pr-review-loopgit clone --depth 1 https://github.com/gabonio/agent-operator-toolkitWrote 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.
[](https://agentmods.dev/skills/gabonio/agent-operator-toolkit/pr-review-loop)<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>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.
| Model | Per session | Once 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 |
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.
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.
- 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
mainormaster. - Record the starting head, diff boundary, repository status, checks available, and any pre-existing review comments. Protect unrelated changes throughout the loop.
- 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.
- Start an iteration counter at one. Never exceed ten without a new user decision.
- 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.
- 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:lineanchor. - 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.
- Verify each finding against code, tests, specifications, and local rules. Classify it as
fix,false positive,duplicate,accepted risk, oruser decision. - 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.
- 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.
- 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.
- 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.
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.
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.
- 3d ago First seen · 24 lines · 69 tokens per session scan A df8f5c487c12
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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