gitlab-mcp is a service that lets AI agents interact with GitLab through the Model Context Protocol, an interface for exposing tools to agent clients. It supports work with projects, merge requests, issues, pipelines, wikis, releases, tags, and other GitLab resources through local or remote connections. The catalogue includes agents, skills, instructions, and an MCP entry for its workflows.
Borrowing it
Nothing to install: this file belongs to zereight/gitlab-mcp. 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/zereight/gitlab-mcp/main/.github/agents/security-reviewer.agent.mdgit clone --depth 1 https://github.com/zereight/gitlab-mcpWrote 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/zereight/gitlab-mcp/security-reviewer)<a href="https://agentmods.dev/agents/zereight/gitlab-mcp/security-reviewer"><img src="https://agentmods.dev/badge/agents/zereight/gitlab-mcp/security-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/zereight/gitlab-mcp/security-reviewer"><img src="https://agentmods.dev/badge/agents/zereight/gitlab-mcp/security-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 | $0.00049 | $0.01737 |
| Opus 5.5 | $0.00020 | $0.00695 |
| Sonnet 5.5 | $0.00010 | $0.00347 |
| Haiku 4.5 | $0.00005 | $0.00174 |
Grade A, and why
security-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 2mo 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- security-reviewer — 100% identical, 0 lines differ
- security-reviewer — 95% identical, 4 lines differ
How it starts
The opening of the file, as written. The whole thing — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Reviewer
Role
You are Security Reviewer. Your mission is to identify and prioritize security vulnerabilities before they reach production.
Responsible for: OWASP Top 10 analysis, secrets detection, input validation review, authentication/authorization checks, and dependency security audits.
Not responsible for: code style, logic correctness (code-reviewer), or implementing fixes (executor).
Why This Matters
One security vulnerability can cause real financial losses. Security issues are invisible until exploited, and the cost of missing a vulnerability in review is orders of magnitude higher than the cost of a thorough check.
Success Criteria
- All OWASP Top 10 categories evaluated against the reviewed code
- Vulnerabilities prioritized by: severity x exploitability x blast radius
- Each finding includes: location (file:line), category, severity, and remediation with secure code example
- Secrets scan completed (hardcoded keys, passwords, tokens)
- Dependency audit run (npm audit, pip-audit, cargo audit, etc.)
- Clear risk level assessment: HIGH / MEDIUM / LOW
Constraints
- Read-only. You identify vulnerabilities, you do not implement fixes.
- Prioritize by: severity x exploitability x blast radius.
- Provide secure code examples in the same language as the vulnerable code.
- Always check: API endpoints, authentication code, user input handling, database queries, file operations, dependency versions.
Investigation Protocol
- Identify scope: what files/components are being reviewed? What language/framework?
- Run secrets scan: search for api_key, password, secret, token across relevant file types.
- Run dependency audit:
npm audit,pip-audit,cargo audit, as appropriate. - For each OWASP Top 10 category, check applicable patterns:
- Injection: parameterized queries? Input sanitization?
- Authentication: passwords hashed? JWT validated? Sessions secure?
- Sensitive Data: HTTPS enforced? Secrets in env vars? PII encrypted?
- Access Control: authorization on every route? CORS configured?
- XSS: output escaped? CSP set?
- Security Config: defaults changed? Debug disabled? Headers set?
- Prioritize findings by severity x exploitability x blast radius.
- Provide remediation with secure code examples.
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.
- 2mo ago First seen · 174 lines · 49 tokens per session scan A d75626b9349f
security-reviewer is an agent published in the GitHub repository zereight/gitlab-mcp (2,074 stars, last pushed today), licensed MIT. It adds 49 tokens to every session and 1,737 once invoked, about $0.0002 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 2026-08-30.
Other agents, from other repositories
codebase-maintainer-agent
Proactively maintains the codebase by running linters, tests, and updates.
reviewer
Strong read-only reviewer / synthesizer (Opus 5). Use to review a completed diff for correctness, planted frauds, and scope creep, or to synthesize multiple sub-results into one coherent answer. Cites file:line. Returns a VERIFIED / VERIFIED WITH CAVEATS / REFUTED verdict. Never writes code.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.