gitlab-mcp: Skill for Claude Code

.github/skills/trace/SKILL.md

trace is a skill for Claude Code from zereight/gitlab-mcp. It costs 33 tokens per session (350 once invoked), scanned A, original, MIT.

An evidence-based investigation workflow for explaining why a software event happened. It compares different possible causes and records supporting evidence, missing information, and the next check that would distinguish them.

In plain words
What is it for?
Use it for runtime bugs, regressions, performance issues, configuration problems, architecture investigations, and postmortems.
Why use it?
It prevents a quick guess from being treated as the root cause. The investigation keeps code, configuration, environment, and measurement problems in consideration.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter.

This is zereight/gitlab-mcp's own configuration. It tells Claude Code how to work on gitlab-mcp itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything gitlab-mcp configures →

About the project

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.

zereight/gitlab-mcp · 2,047 stars · on GitHub · zereight.github.io

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/zereight/gitlab-mcp/main/.github/skills/trace/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/zereight/gitlab-mcp

Made for: Claude Code.

Wrote 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.

agentmods badge for trace

README.md
[![agentmods](https://agentmods.dev/badge/skills/zereight/gitlab-mcp/trace/github.svg)](https://agentmods.dev/skills/zereight/gitlab-mcp/trace)
Your own site
<a href="https://agentmods.dev/skills/zereight/gitlab-mcp/trace"><img src="https://agentmods.dev/badge/skills/zereight/gitlab-mcp/trace/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.

agentmods 80×15 button for trace

Your own site · 80×15
<a href="https://agentmods.dev/skills/zereight/gitlab-mcp/trace"><img src="https://agentmods.dev/badge/skills/zereight/gitlab-mcp/trace.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 350 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00033 $0.00350
Opus 5.5 $0.00013 $0.00140
Sonnet 5.5 $0.00007 $0.00070
Haiku 4.5 $0.00003 $0.00035

Measured 1mo ago against content hash fb21957a1ad7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

trace 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.

Origin

Copies of this mod

2 near-identical copies found in the catalogue:

  • trace — 100% identical, 0 lines differ
  • trace — 100% identical, 0 lines differ
.github/skills/trace/SKILL.md · 54 lines

What it actually says

Trace

Evidence-driven causal tracing using competing hypotheses. Use for ambiguous, causal, evidence-heavy questions where the goal is to explain WHY something happened.

Good Entry Cases

  • Runtime bugs and regressions
  • Performance / latency behavior
  • Architecture / premortem / postmortem analysis
  • Config / routing / orchestration behavior
  • "Given this output, trace back the likely causes"

Core Contract

Always preserve: Observation → Hypotheses → Evidence For → Evidence Against → Best Explanation → Critical Unknown → Discriminating Probe

Workflow

  1. Restate the observed result precisely
  2. Generate 3 deliberately different hypotheses:
    • Code-path / implementation cause
    • Config / environment / orchestration cause
    • Measurement / artifact / assumption mismatch
  3. Assign @tracer to each hypothesis lane
  4. Each lane: evidence for, evidence against, critical unknown, discriminating probe
  5. Apply lenses: Systems, Premortem, Science
  6. Rebuttal round between top two hypotheses
  7. Rank, detect convergence, synthesize

Output

### Observed Result
[What happened]

### Ranked Hypotheses
| Rank | Hypothesis | Confidence | Evidence Strength |
|------|------------|------------|-------------------|

### Most Likely Explanation
[Current best explanation]

### Critical Unknown
[Single missing fact]

### Recommended Discriminating Probe
[Single next probe]
Changes

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.

  1. 1mo ago First seen · 54 lines · 33 tokens per session scan A fb21957a1ad7

Subscribe to this mod's changes

trace 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 350 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.

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