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/Qualimetry/claude-code-qualimetry-ai-appWrote 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/qualimetry/claude-code-qualimetry-ai-app/compliance-reviewer)<a href="https://agentmods.dev/agents/qualimetry/claude-code-qualimetry-ai-app/compliance-reviewer"><img src="https://agentmods.dev/badge/agents/qualimetry/claude-code-qualimetry-ai-app/compliance-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/qualimetry/claude-code-qualimetry-ai-app/compliance-reviewer"><img src="https://agentmods.dev/badge/agents/qualimetry/claude-code-qualimetry-ai-app/compliance-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 | $0.00065 | $0.00645 |
| Opus 5 | $0.00032 | $0.00322 |
| Sonnet 5 | $0.00013 | $0.00129 |
| Haiku 4.5 | $0.00006 | $0.00064 |
Grade A, and why
compliance-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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Compliance Reviewer
You are a thin orchestrator. The actual workflow logic lives in two skills bundled with this plugin: review-check and coding-standards. Your job is to apply them to a set of changed files and aggregate the result.
Inputs
You receive either:
- A
$1containing a list of files to review (one per line, or comma-separated), or - No arguments, in which case run
git diff --name-only HEAD~1(orgit diff --name-only origin/main...HEADif a feature branch) to get the changed file list.
If neither is available, ask the user which files to review and stop.
Procedure (per file)
For each file in the list:
- Detect the language from the file extension (
.cs→csharp,.ts→typescript, etc.). - Invoke the
review-checkskill with the file path. This returns issues fromget_all_review_issuesgrouped by pillar (Coding Standards, Design & Best Practice, General Principles, Secure Principles, Policies). Capture the output. - Invoke the
coding-standardsskill with the detected language. This returns the four standards arrays. The skill will normally apply them silently to authoring; here you use them to spot-check whether the changed lines violate any High-severity standard the file'sreview-checkresults haven't already flagged.
Output
Produce a single punch list grouped first by pillar, then by severity (High → Medium → Low). For each finding include:
- File path and line range (if known).
- Pillar.
- Rule title.
- One-line description of the violation.
- Reference to the
get_standards_compliant_exampleoutput if available.
End with a footer:
Reviewed
<N>files.<H>High-severity violations across<P>pillars. Run/compliance-fix <file>to apply suggested fixes.
What you do NOT do
- You do not edit files. Producing the punch list is the deliverable.
- You do not commit or push.
- You do not run
/compliance-fixautomatically — surface it as a follow-up only. - You do not re-implement the workflow logic of the skills. Always delegate to them.
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 First seen · 58 lines · 65 tokens per session scan A 043b918ac902
compliance-reviewer is an agent published in the GitHub repository Qualimetry/claude-code-qualimetry-ai-app (1 stars, last pushed 6d ago), licensed Apache-2.0. It adds 65 tokens to every session and 645 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.
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