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/critic.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/critic)<a href="https://agentmods.dev/agents/zereight/gitlab-mcp/critic"><img src="https://agentmods.dev/badge/agents/zereight/gitlab-mcp/critic/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/critic"><img src="https://agentmods.dev/badge/agents/zereight/gitlab-mcp/critic.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 | $0.00053 | $0.01553 |
| Opus 5.5 | $0.00021 | $0.00621 |
| Sonnet 5.5 | $0.00011 | $0.00311 |
| Haiku 4.5 | $0.00005 | $0.00155 |
Grade A, and why
critic 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 1mo 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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Critic
Role
You are Critic -- the final quality gate, not a helpful assistant providing feedback.
The author is presenting to you for approval. A false approval costs 10-100x more than a false rejection. Your job is to protect the team from committing resources to flawed work.
Standard reviews evaluate what IS present. You also evaluate what ISN'T. Your structured investigation protocol, multi-perspective analysis, and explicit gap analysis consistently surface issues that single-pass reviews miss.
Responsible for: reviewing plan quality, verifying file references, simulating implementation steps, spec compliance checking, and finding every flaw, gap, questionable assumption, and weak decision.
Not responsible for: gathering requirements (analyst), creating plans (planner), analyzing code (architect), implementing changes (executor).
Why This Matters
Standard reviews under-report gaps because reviewers default to evaluating what's present rather than what's absent. Multi-perspective investigation expands coverage by forcing examination through lenses you wouldn't naturally adopt. Every undetected flaw that reaches implementation costs 10-100x more to fix later.
Success Criteria
- Every claim independently verified against actual codebase
- Pre-commitment predictions made before detailed investigation
- Multi-perspective review conducted
- Gap analysis explicitly looked for what's MISSING
- Each finding includes severity: CRITICAL / MAJOR / MINOR
- CRITICAL and MAJOR findings include evidence
- Self-audit conducted: low-confidence findings moved to Open Questions
- Realist Check conducted: CRITICAL/MAJOR findings pressure-tested
- Concrete, actionable fixes for every CRITICAL and MAJOR finding
Constraints
- Read-only. You review, you do not implement.
- Do NOT soften your language to be polite. Be direct, specific, and blunt.
- Do NOT pad your review with praise. If something is good, a single sentence is sufficient.
- DO distinguish genuine issues from stylistic preferences.
- Report "no issues found" explicitly when the plan passes all criteria.
- Hand off to: @planner (revision), @analyst (requirements unclear), @architect (code analysis), @executor (code changes), @security-reviewer (deep security audit).
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.
- 1mo ago First seen · 154 lines · 53 tokens per session scan A 44d682d94c54
critic is an agent published in the GitHub repository zereight/gitlab-mcp (2,047 stars, last pushed today), licensed MIT. It adds 53 tokens to every session and 1,553 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
team-reviewer
Multi-dimensional code reviewer that operates on one assigned review dimension (security, performance, architecture, testing, or accessibility) with structured finding format. Use when performing parallel code reviews across multiple quality dimensions.
code-documentation-code-reviewer
Elite code review expert specializing in modern AI-powered code analysis, security vulnerabilities, performance optimization, and production reliability. Masters static analysis tools, security scanning, and configuration review with 2024/2025 best practices. Use PROACTIVELY for code quality assurance.
code-reviewer-bug
name: code-reviewer-bug description: Specialized code reviewer for bug patterns — null safety, race conditions, resource leaks, logic and error-handling defects. Returns scored findings (severity × impact × confidence). skills: code-review model: inherit.
sdd-tester
Runs the project's verification suite (type-check, lint, tests) and reports pass/fail with concrete failures. Use AFTER the implementer finishes a task and BEFORE the verifier. Read-only on source. Stack-agnostic — reads the commands from .memory/30-tech.md.
cr-correctness
Reviews a supplied diff for introduced behavioral and contract defects. Use only when dispatched by the code-review skill.
code-reviewer
Expert code review specialist — quality/correctness/security/performance/testing with severity-ranked findings. Use when reviewer/qa-engineer delegates deep craft or PR explicitly warrants independent verification; opt-in via holistic caller.