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/skills/plan/SKILL.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/skills/zereight/gitlab-mcp/plan)<a href="https://agentmods.dev/skills/zereight/gitlab-mcp/plan"><img src="https://agentmods.dev/badge/skills/zereight/gitlab-mcp/plan/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/zereight/gitlab-mcp/plan"><img src="https://agentmods.dev/badge/skills/zereight/gitlab-mcp/plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00033 | $0.00462 |
| Opus 5.5 | $0.00013 | $0.00185 |
| Sonnet 5.5 | $0.00007 | $0.00092 |
| Haiku 4.5 | $0.00003 | $0.00046 |
Grade A, and why
plan 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- plan — 100% identical, 0 lines differ
What it actually says
Plan
Creates comprehensive, actionable work plans through intelligent interaction. Auto-detects whether to interview (broad requests) or plan directly (detailed requests).
Modes
| Mode | Trigger | Behavior |
|---|---|---|
| Interview | Default for broad requests | Interactive requirements gathering |
| Direct | --direct, or detailed request |
Skip interview, generate plan directly |
| Consensus | --consensus, "ralplan" |
Planner → Architect → Critic loop |
| Review | --review |
Critic evaluation of existing plan |
Interview Mode (broad/vague requests)
- Classify request: broad triggers interview
- Ask ONE focused question at a time for preferences, scope, constraints
- Gather codebase facts via @explore BEFORE asking user
- Consult @analyst for hidden requirements
- Create plan when user signals readiness
Direct Mode (detailed requests)
- Optional brief @analyst consultation
- Generate comprehensive work plan immediately
Consensus Mode (--consensus / "ralplan")
- @planner creates initial plan with RALPLAN-DR summary (Principles, Decision Drivers, Options)
- @architect reviews for architectural soundness (sequential, NOT parallel with critic)
- @critic evaluates quality criteria (after architect completes)
- Re-review loop (max 5 iterations) if critic rejects
- Apply improvements on approval
- Final plan includes ADR (Decision, Drivers, Alternatives, Why chosen, Consequences)
Review Mode (--review)
- Read plan from
.omc/plans/ - @critic evaluates
- Return verdict: APPROVED / REVISE / REJECT
Output
Plans saved to .omc/plans/. Include:
- Requirements Summary
- Testable Acceptance Criteria
- Implementation Steps (with file references)
- Risks and Mitigations
- Verification Steps
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 · 54 lines · 33 tokens per session scan A c9bd134f1392
plan is a skill published in the GitHub repository zereight/gitlab-mcp (2,047 stars, last pushed today), licensed MIT. It adds 33 tokens to every session and 462 once invoked, about $0.0001 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 skills, from other repositories
gitlab-merge-request-review
Review and merge GitLab merge requests via the gitlab-api MCP server — by default the MRs assigned to you or where you are a reviewer, optionally scoped to a project, group, or the whole instance. Read an MR, gate it on a green pipeline (pipeline → jobs → job log), then approve, accept/merge, or set…
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CI/CD pipeline review on GitLab via the gitlab-api MCP server — review pipeline results for a project, a group, or the whole instance, drill into the CI jobs of a pipeline, and read a job's log; also trigger a pipeline on a ref. Use when the agent must review CI results across a project/group/organization, check…
gitlab-vulnerabilities
Dependency and security-vulnerability review on GitLab via the gitlab-api MCP server — the GitLab counterpart to GitHub Dependabot. Read a project's Dependency List, review a project's or group's security vulnerabilities/findings, and fetch a single vulnerability by ID. Use when the agent must audit a project's…
gitlab-issues
Issue review and tracking on GitLab via the gitlab-api MCP server — review a project's issues, review issues across a whole group/organization, and read, create, update, or close an issue with the domain-typed tool. Use when the agent must triage a project's issues, see every issue affecting a group, open a new issue…
gitlab-merge-request-create
Open a new GitLab merge request against a project via the gitlab-api MCP server — from a source branch into a target branch, with title, description, assignees, reviewers, labels, and remove-source-branch/squash options. Use when the agent must create/open an MR for a project. Do NOT use to review, approve, or merge…
browser-qa
Use when you need lightweight browser QA for a web page, local HTML file, or app: inspect console errors, broken assets, keyboard/focus behavior, viewport readability, and publish evidence-backed findings JSON through a local HTML report viewer.