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 spencermarx/open-code-review --skill ocr-review-loopgit clone --depth 1 https://github.com/spencermarx/open-code-reviewWrote 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/spencermarx/open-code-review/ocr-review-loop)<a href="https://agentmods.dev/skills/spencermarx/open-code-review/ocr-review-loop"><img src="https://agentmods.dev/badge/skills/spencermarx/open-code-review/ocr-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/spencermarx/open-code-review/ocr-review-loop"><img src="https://agentmods.dev/badge/skills/spencermarx/open-code-review/ocr-review-loop.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 90 Skill allows unbounded resource consumption (API calls, storage, compute). Without rate limits or quotas, a compromised or misbehaving agent can cause denial-of-service or cost overruns.Fix: Set explicit rate limits, timeouts, and resource quotas for API calls, file operations, and compute. Implement circuit breakers for runaway loops.
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 | $0.00178 | $0.01723 |
| Opus 5.5 | $0.00071 | $0.00689 |
| Sonnet 5.5 | $0.00036 | $0.00345 |
| Haiku 4.5 | $0.00018 | $0.00172 |
Grade A, and why
OCR Review-to-Approval 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OCR Review-to-Approval Loop
What This Skill Does
Orchestrates an autonomous review → address → re-review loop on a pull request, using OCR's existing multi-agent review pipeline, until the review reaches an APPROVE verdict — then runs one final address pass for leftover suggestions. Every review and every address round is posted to the GitHub PR as a comment, producing a transparent, reviewable audit trail.
It is a thin orchestrator over two skills it does not reimplement:
/ocr:review→.ocr/commands/review.md(the 8-phase multi-agent review that emits a verdict)/ocr:address→.ocr/commands/address.md(corroborate feedback against code, then implement)
When to Use
- "Review and address in a loop until it's approved."
- "Iterate /ocr:review and /ocr:address on this PR."
- "Auto review-and-fix PR #N to a clean approval."
When NOT to Use (use the underlying skills directly)
- A single review with no auto-fixing →
/ocr:review. - Addressing one existing review's feedback →
/ocr:address. - There is no PR / not on a feature branch (this skill commits and posts).
Prerequisites
- On a non-default git branch with an open GitHub PR (the loop commits + pushes each round).
ghCLI installed and authenticated (for posting; skip with--no-post).- OCR set up in the repo (
.ocr/exists,ocrCLI available). Run/ocr:doctorif unsure. - A green-ish working tree: any uncommitted changes will become part of what is reviewed.
Arguments
/ocr-review-loop [pr] [--team <spec>] [--max-rounds N] [--no-final-suggestions] [--no-post]
pr(optional): PR number. Default: the open PR for the current branch.--team <spec>(optional): reviewer team override (reviewer-id:count,...), forwarded to/ocr:review. Default: the project's default team (ocr team resolve).--max-rounds N(optional): safety cap on review rounds. Default: 5. The loop never runs forever.--no-final-suggestions(optional): stop at APPROVE; skip the final suggestions pass.--no-post(optional): run locally; do not post to GitHub. Present the trail in-chat instead.
What ships with it
2 files 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 First seen · 117 lines · 178 tokens per session scan A a23cd80ee010
OCR Review-to-Approval Loop is a skill published in the GitHub repository spencermarx/open-code-review (379 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 178 tokens to every session and 1,723 once invoked, about $0.0007 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 2026-09-03.
Other skills, from other repositories
github-review-pr
Review GitHub pull requests with detailed, multi-perspective code analysis using parallel subagents. Use this skill whenever the user wants to review a PR, asks for code review on a pull request, mentions "review PR", "check this PR", "look at pull request", or references a PR number or GitHub PR URL. Do NOT use for…
github-review-pr
Review a GitHub pull request by number or URL for evidence-backed defects. Not for reviewing local uncommitted changes.
code-reviewer
Review code for best practices, bugs, and security issues.
audit-pr
Audit a whole PR against the delivery contract and return MERGE-READY or evidenced blockers with the full URL. Consumes the current review-change REVIEW-PASS receipt instead of re-running review axes; posts a SHA-bound ready comment; never edits or merges. Triggers: "audit-pr", "is this PR ready", "merge gate".
github-code-review
Review PRs: diffs, inline comments via gh or REST.
git-monorepo-release
A release workflow for a monorepo—a single repository containing several packages that can each have their own version.