Borrowing it
Nothing to install: this file belongs to matlab/mcp-framework-matlab-production-server. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/matlab/mcp-framework-matlab-production-server/main/.claude/skills/mps-review/SKILL.mdgit clone --depth 1 https://github.com/matlab/mcp-framework-matlab-production-serverWrote 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/matlab/mcp-framework-matlab-production-server/mps-review)<a href="https://agentmods.dev/skills/matlab/mcp-framework-matlab-production-server/mps-review"><img src="https://agentmods.dev/badge/skills/matlab/mcp-framework-matlab-production-server/mps-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/matlab/mcp-framework-matlab-production-server/mps-review"><img src="https://agentmods.dev/badge/skills/matlab/mcp-framework-matlab-production-server/mps-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high Prompt Injection · line 82 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00022 | $0.01739 |
| Opus 5 | $0.00011 | $0.00870 |
| Sonnet 5 | $0.00004 | $0.00348 |
| Haiku 4.5 | $0.00002 | $0.00174 |
Grade A, and why
mps-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 — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review and Publish to Reviews Branch
You are helping the user run a code review on the current branch and publish the results to the reviews branch so the review-gate CI check can pass.
Step 1: Determine the PR Number
If the user provided a PR number as an argument, use that.
Otherwise, derive it from the current branch:
git branch --show-current
The PR number may be embedded in the branch name (e.g., feature/PR-21-description) or you may need to ask the user. If you cannot determine the PR number, ask the user to provide it.
Step 2: Run the Code Review
Review the current branch's changes against main directly. Do NOT use gh or the /review skill — they are unavailable in this environment.
First, determine the review scope:
git log --oneline main..HEAD
Scope rules:
- If there are 10 or fewer commits, review the full diff:
git diff main..HEAD - If there are more than 10 commits, ask the user which commits to review, or default to the most recent 5:
git diff HEAD~5..HEAD - If the user specified a commit range, use that
Then perform a thorough code review of the diff, covering:
- Code correctness and potential bugs
- Following project conventions
- Performance implications
- Test coverage
- Security considerations
Test coverage expectation: If the diff introduces new public functions (new .m files outside of Test/ and +test/ directories), check whether corresponding tests are also included. If new public functions are added without new or modified test files, flag this in the review as a finding:
- List each new public function that lacks test coverage in the diff
- State clearly that the author must explain in their Review Response why tests are not included (acceptable reasons: covered by existing tests, test PR planned separately, internal helper not directly testable)
- This is NOT an automatic rejection — it is a required explanation. The review-gate will pass once the author provides their response.
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 First seen · 166 lines · 22 tokens per session scan A 3273e5de3aa3
mps-review is a skill published in the GitHub repository matlab/mcp-framework-matlab-production-server (31 stars, last pushed 5d ago), licensed BSD-3-Clause. It adds 22 tokens to every session and 1,739 once invoked, about $0.0001 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 2026-09-05.
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