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/mthines/agent-skills/review-loopnpx skills add mthines/agent-skills --skill review-loopgit clone --depth 1 https://github.com/mthines/agent-skillsWrote 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/mthines/agent-skills/review-loop)<a href="https://agentmods.dev/skills/mthines/agent-skills/review-loop"><img src="https://agentmods.dev/badge/skills/mthines/agent-skills/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 | $0.00431 | $0.10634 |
| Opus 5 | $0.00216 | $0.05317 |
| Sonnet 5 | $0.00086 | $0.02127 |
| Haiku 4.5 | $0.00043 | $0.01063 |
Grade A, and why
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 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.
How it starts
The opening of the file, as written. The whole thing — 702 lines — stays where its author put it; the contents beside it link to each section on GitHub.
review-loop — Bounded Review-Apply-Resolve Convergence
Drive a PR from its initial draft state to a clean, review-ready state by
iterating pr-reviewer → implement-suggestion --resolve-all → polish simplify
until every review thread is resolved or the cap is reached, then refresh the
PR description to match the shipped diff.
A thread is resolved when it is either fixed (a code change landed) or answered (a reply — the answer to a question, the agent's take on a discussion, or a rationale for a declined suggestion). The only threads left open at convergence are genuine human-judgment flags: a real potential issue the agent will neither auto-apply nor honestly decline. That safety valve means the loop can never green-wash a PR by resolving a live finding — it surfaces it instead.
This skill is an orchestrator. It contains no quality rules of its own. It sequences existing pieces, each owning its own domain:
pr-reviewer— finds issues (read-only; posts oneCOMMENTreview; on a re-review resolves its own addressed threads).implement-suggestion --resolve-all— applies actionable findings and replies-to-and-resolves the non-fix threads it can honestly close (single-shot, no--watch).Skill("polish", "simplify")— applies Class M mechanical refactors behind a confidence gate.ci-auto-fix— diagnoses and fixes a red check after the iteration's push (skipped under--no-ci).- On convergence — refreshes the PR description (via the shared description-contract) and, best-effort, notes the linked Linear ticket.
Under --external-review, step 1 is replaced by a wait: the reviewer is
another process (a review bot, a CI-triggered agent, a teammate), and the loop
polls for its output instead of producing its own. Steps 2–5 are unchanged —
they consume threads from GitHub and do not care who wrote them.
Dispatch mechanics — read before invoking
pr-reviewer is an agent, not a skill. Dispatch it with the Task tool
(Task(subagent_type="pr-reviewer", prompt="<PR-URL> [--critical]")). Do not call
Skill("pr-reviewer", …) — there is no skill by that name and it errors with
Unknown skill: pr-reviewer.
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.
- 2d ago Changed · +60 lines · +58 tokens per session 508466e977f6
- 5d ago First seen · 642 lines · 373 tokens per session scan A c74f5767968e
review-loop is a skill published in the GitHub repository mthines/agent-skills (12 stars, last pushed today), licensed MIT. It adds 431 tokens to every session and 10,634 once invoked, about $0.0022 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.
Other skills, from other repositories
ego-browser
Skill "ego-browser" from citrolabs/ego-lite, covering ego-browser, quick start, common helpers, task spaces and control handoff.
temporal-developer
Develop, debug, and manage Temporal applications across Python, TypeScript, Go, Java, .NET, Ruby, and Rust. Use when the user is building workflows, activities, or workers with a Temporal SDK, debugging issues like non-determinism errors, stuck workflows, or activity retries, using Temporal CLI, Temporal Server, or…
x-algorithm
Write X (Twitter) posts that the For You algorithm actually rewards. Grounded in the open-sourced X recommendation system — the Grok-based transformer ranker, Phoenix retrieval, Thunder in-network store, and Grox content-understanding pipeline. Use when the user wants to write a post, thread, reply, or quote; plan a…
opencode-memory
Browse local OpenCode history: sessions, messages, plans, prompt history, and prior decisions. Use when the user says history, previous session, last time, remember, recall, plans, prior work, or when resuming/debugging repeated work where earlier OpenCode context may help. Do not use for fresh tasks or when current…
creating-explainers
Use when creating an interactive explainer - a single self-contained HTML page with hand-built Canvas figures. Handles source-file explainers, topic-driven research explainers, and mixed intake where files provide the spine and research adds support. Trigger phrases include "make an explainer", "turn this paper into…
custom-icons
Create or refine custom icon assets as native or traced SVGs and transparent PNG/WebP files. Use when the user asks for a bespoke icon or cohesive icon set, wants an image traced into a clean vector, or needs a detailed or 3D icon with transparency.