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 skills add Parcha-ai/parcha-skills --skill review-loopgit clone --depth 1 https://github.com/Parcha-ai/parcha-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/parcha-ai/parcha-skills/review-loop)<a href="https://agentmods.dev/skills/parcha-ai/parcha-skills/review-loop"><img src="https://agentmods.dev/badge/skills/parcha-ai/parcha-skills/review-loop/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.
<a href="https://agentmods.dev/skills/parcha-ai/parcha-skills/review-loop"><img src="https://agentmods.dev/badge/skills/parcha-ai/parcha-skills/review-loop.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00118 | $0.02847 |
| Opus 5.5 | $0.00047 | $0.01139 |
| Sonnet 5.5 | $0.00024 | $0.00569 |
| Haiku 4.5 | $0.00012 | $0.00285 |
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 1mo 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 — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review loop
This skill has one job: take a GitHub PR with open review threads and drive every thread, from
every reviewer, to zero unresolved, iterating until the target is met, then report what it did
in a fixed format. It does not QA the running application; that is autoqa's job. It does not
decide whether the diff is safe beyond what reviewers raised; that is blast-radius's job. It
does not merge, and it does not mint credentials.
Inputs
| Input | Required | Default |
|---|---|---|
Repository (owner/repo) |
no | The origin remote of the current checkout |
| PR number | no | The PR for the current branch (gh pr view) |
Target (open-for-review, review-clean, or merge-ready) |
no | review-clean |
| Trigger comment text | no | @greptile-apps review |
--max-iterations N |
no | None (no cap). Set only when the caller wants a hard stop |
| Gate command | no | None. The caller or the repository supplies the command that runs tests and lint (for example the repo's make check); the skill only says where in the loop it runs |
| Base-branch sync | no | None. The caller or repository supplies the rebase or merge policy; the skill says where it runs |
Auth precondition: the caller has authenticated gh before invoking this skill. The skill
never mints, reads, or stores tokens. If gh auth status fails, stop and report it.
Iteration
Repeat until the target in step 9 is met. There is no iteration cap by default; a caller may
pass --max-iterations to impose one. The loop still stops on timeout, a red gate it cannot
fix, an auth failure, or a stall (see "Stop on stall"). Each iteration:
- Sync with the base branch if the caller supplied a sync policy. Run the gate command when the head changed or no exact-head result exists. Reuse valid exact-head evidence. A red gate stops the iteration; fix the gate before touching review comments.
- Fetch every open thread. See "Fetching everything". Do not filter to one reviewer.
- Triage by content, not by author. For each thread decide: actionable (a code change is needed), informational (no change, reply explains why), or false positive (reply explains why). Record the decision. A reply that proves inherited behavior or base parity without a code push keeps prior exact-head evidence valid. Do not rerun gates or restart proof and description work.
- Fix every actionable item in one pass. Read the file at the cited line, understand the comment in context, make the change.
- If code changed, run the gate command again. Do not push a red gate.
- If code changed, commit and push. Commit message names the iteration, for example
Address review feedback (review-loop iteration 2). - Reply and resolve. See "Human threads" and "Bot threads". A reply goes on the thread that raised the point, not in a new top-level comment.
- Re-request review once per push. A reply without a push does not require another request. See "Greptile specifics" and "Devin specifics". Wait for the results with a bounded poll.
- Check the target. For
review-cleanormerge-ready, require zero unresolved threads across every reviewer and, when Greptile is installed, a 5/5 score from its latest summary. Foropen-for-review, require a non-draft PR and focused proof. Automated review may remain pending.
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.
- 1mo ago Changed · +8 lines · +6 tokens per session 313bb9fbc5dc
- 1mo ago Changed · +12 lines a99b365c9d3f
- 1mo ago First seen · 183 lines · 112 tokens per session scan A cacabae7aeaf
review-loop is a skill published in the GitHub repository Parcha-ai/parcha-skills (126 stars, last pushed 15d ago), licensed MIT. It adds 118 tokens to every session and 2,847 once invoked, about $0.0005 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 2026-09-17.
review-loop compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| review-loopParcha-ai/parcha-skills | Skill | 126 | 15d ago | MIT | A | 118 | Claude Code |
| autoreviewopenclaw/clawhub | Skill | 9.5k | today | MIT | A | 17 | Claude Code, Codex |
| agent-teams-simplify-and-hardenLeoYeAI/openclaw-master-skills | Skill | 2.2k | 6d ago | MIT | A | 115 | Claude Code, Codex |
| omh-code-reviewrlaope/oh-my-hermes | Skill | 5.2k | today | MIT | A | 48 | Claude Code, Codex |
| revdiff-planumputun/revdiff | Skill | 947 | 2d ago | MIT | A | 84 | Claude Code |
| explore-unknownsdzhng/skills | Skill | 1.4k | today | MIT | A | 162 | Claude Code, Codex |
| re0-mergeLilMGenius/paperthin | Skill | 1.4k | 4d ago | MIT | A | 70 | Claude Code |