Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add Jose-Ribeir/claude-code-review-gate/plugin install review-gateWrote 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/jose-ribeir/claude-code-review-gate/review)<a href="https://agentmods.dev/skills/jose-ribeir/claude-code-review-gate/review"><img src="https://agentmods.dev/badge/skills/jose-ribeir/claude-code-review-gate/review/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/jose-ribeir/claude-code-review-gate/review"><img src="https://agentmods.dev/badge/skills/jose-ribeir/claude-code-review-gate/review.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 | $0.00070 | $0.05755 |
| Opus 5 | $0.00035 | $0.02877 |
| Sonnet 5 | $0.00014 | $0.01151 |
| Haiku 4.5 | $0.00007 | $0.00575 |
Grade A, and why
review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 456 lines — stays where its author put it; the contents beside it link to each section on GitHub.
review-gate — orchestrator
You are orchestrating an AI code review. Follow these steps exactly.
0. Parse arguments ($ARGUMENTS)
--staged— review staged changes only (git diff --staged).--unpushed— review all commits not yet pushed to the upstream branch. File list:git diff -M @{u}..HEAD --name-status; falls back togit diff -M origin/main..HEAD --name-statusif no upstream tracking branch is set. Per-file diff:git diff -M @{u}..HEAD -- <path>(or the fallback ref).--range <A>..<B>— review exactly that range. Takes precedence over--unpushed. The pre-push gate passes it, because git tells a pre-push hook precisely what is being sent and where (<local ref> <local sha> <remote ref> <remote sha>on stdin), and that is a different question from "is HEAD ahead of its own upstream". They diverge whenever you push to a ref that is not your upstream —git push origin mybranch:mainwithmybranchalready pushed has nothing unpushed by the@{u}reading, so deriving the range here would review nothing while five commits reachedmain.--scan— full-file scan of the repo (or ofpathsif given) instead of a diff review.--json— print ONLY the machine-readable JSON output object (no prose). The push gate relies on this. Without it, print a human-readable report.--rule <path>— explicit rule file (highest precedence).--summary— also produce a project summary (implied by--scan).- Any non-flag arguments are treated as path filters (files or directories).
What ships with it
7 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.
- 4d ago Changed · +13 lines 22ef508ce088
- 9d ago First seen · 443 lines · 70 tokens per session scan A 34d0e48a2ff1
review is a skill published in the GitHub repository Jose-Ribeir/claude-code-review-gate (3 stars, last pushed 7d ago), licensed Apache-2.0. It adds 70 tokens to every session and 5,755 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.
Other skills, from other repositories
rami-code-review
Run the Rami review loop on a PR — fetch findings, fix or rebut each by severity, push, repeat until readyforreview is true. Invoked by /rami:review and auto-triggered when the user asks for "rami review", "review my PR", "fix all rami issues", or similar.
rami-rebut-finding
Use when the user wants to challenge, rebut, or dispute a Rami code review finding — phrases like "rebut this", "this is a false positive", "Rami is wrong about X", "tell Rami this is intentional". Walks through the right MCP tool to use, the four valid rebut reasons, and what to do when Rami rejects the rebuttal.
rami-review-status
Check the current Rami review status without triggering a new review. Use when the user asks whether a Rami review is finished, ready, blocked, queued, or in progress.
java-cache
Use when the user asks to add caching, configure Redis or Caffeine cache, use @Cacheable/@CacheEvict/@CachePut, optimize repeated database or API calls, or review existing Spring Boot cache configuration.
java-jpa
Reviews Spring Data JPA for N+1 queries, fetch strategies, projections, and Specifications. Use when user asks to "review JPA", "check for N+1", "JPA performance", "review my entities", "check fetch strategy", or "review my repositories".
java-health
Runs a holistic code health check scoring Security, Tests, Performance and Quality with A-F grades. Use when user asks to "check health", "score this project", "health check", "how good is this code", "overall assessment", or "code quality score".