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AC gitlab-skills

Manage GitLab projects from the command line — list/inspect projects, list and create issues, list/create/merge merge requests, and list or trigger CI/CD pipelines. Use this whenever the user wants to work with a GitLab repo, file an issue, open or merge an MR, or kick off / check a pipeline on GitLab.com or a self-hosted GitLab.

ClawHub Agent Skills author: weiguang1017 v0.1.0 MIT-0 8 files body ≈ 574 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Manage GitLab projects from the command line — list/inspect projects, list and create issues, list/create/merge merge requests, and list or trigger CI/CD…

As a process C 50/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

ProcedureGitLabInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
C
50/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 50/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 3 mutating operations with no state check
    • 40Consistency. Frontmatter name (gitlab-skills) differs from the folder (gitlab-devops-skill)
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 8 steps
    • 100Execution cost. Instruction body is 574 tokens

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +3Description length 331: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 8 items
    • +4Has examples (2 code blocks)
    • +3All 1 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: suspicious
    This GitLab skill is coherent and disclosed, but it can perform high-impact GitLab write actions with broad implicit activation and limited confirmation guidance.
    LLM: suspicious (high) · 5 Aug 2026