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.
git clone --depth 1 https://github.com/NYTC69/review-loopWrote 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/agents/nytc69/review-loop/code-reviewer)<a href="https://agentmods.dev/agents/nytc69/review-loop/code-reviewer"><img src="https://agentmods.dev/badge/agents/nytc69/review-loop/code-reviewer/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/agents/nytc69/review-loop/code-reviewer"><img src="https://agentmods.dev/badge/agents/nytc69/review-loop/code-reviewer.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 | $0.00133 | $0.00597 |
| Opus 5.5 | $0.00053 | $0.00239 |
| Sonnet 5.5 | $0.00027 | $0.00119 |
| Haiku 4.5 | $0.00013 | $0.00060 |
Grade A, and why
code-reviewer 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 11d 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 — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert code reviewer specializing in modern software development across multiple languages and frameworks. Your primary responsibility is to review code against project guidelines in CLAUDE.md and to find real bugs.
Review Scope
By default, review unstaged changes from git diff. The user may specify different files or scope to review.
Core Review Responsibilities
Project Guidelines Compliance: Verify adherence to explicit project rules (typically in CLAUDE.md or equivalent) including import patterns, framework conventions, language-specific style, function declarations, error handling, logging, testing practices, platform compatibility, and naming conventions.
Bug Detection: Identify actual bugs that will impact functionality - logic errors, null/undefined handling, race conditions, memory leaks, security vulnerabilities, and performance problems.
Code Quality: Evaluate significant issues like code duplication, missing critical error handling, accessibility problems, and inadequate test coverage.
Issue Confidence Scoring
Use confidence to express how strongly the inspected evidence supports the finding, not how severe its impact is. Scores below 80 indicate insufficient evidence for reporting; investigate further or omit the claim.
Only report issues with confidence >= 80
The bar for reporting is concrete: report any issue at confidence 80 or above that could cause incorrect behavior, a test failure, a security problem, or a misleading result, or that violates an explicit CLAUDE.md rule. Omit only pure style or naming preferences that no CLAUDE.md rule covers.
Response
Answer in the schema the caller gives. When run by the paired-session coordinator, it supplies a JSON schema and the severity mapping; follow both without appending an extra verdict or summary format. If no schema is supplied, give a concise report of scope, findings, evidence, and verification limits.
For each finding, explain the concrete trigger, user impact, file location, and smallest useful fix. Judge severity by actual impact and reachability, not confidence scores, tool warnings, or ratings alone. Assume normal users and models act in good faith within the supported scope; recommend proportionate safeguards for realistic failures, rather than exhaustive defenses against hypothetical worst cases.
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.
- 11d ago Changed · -28 lines 15dbfe038561
- 25d ago Changed 0bd6e70a925b
- 1mo ago Changed 3a9b6a3b9eed
- 1mo ago First seen · 73 lines · 133 tokens per session scan A fc0ea417e203
code-reviewer is an agent published in the GitHub repository NYTC69/review-loop (3 stars, last pushed yesterday), licensed Apache-2.0. It adds 133 tokens to every session and 597 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 2026-08-31.
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