SKILLEMALL.ai
GitHub ↗ RU Sign in

BB cicd-aiops

Use this skill whenever the user needs to operate a self-managed GitLab or self-hosted Gitea CI/CD server — a one-shot overview, server version and token identity, projects with storage statistics, pipelines/runs with jobs and trace tails, the runner fleet, merge/pull requests, branches, protection rules and releases, artifact inventories, four flagship RCAs (pipeline failures, runner health & queue, artifact/storage bloat, stale work), and governed writes (retry/cancel a pipeline, pause/resume a runner, delete artifacts, update branch protection). Always use this skill for "GitLab", "Gitea", "pipeline failed", "CI is red", "job trace", "runner offline", "jobs stuck in queue", "artifact storage full", "stale merge requests", "stale branches", "protect the default branch", "retry the pipeline", "cancel the pipeline", "delete old artifacts" when the context is a self-managed GitLab or Gitea instance. Do NOT use when the target is something other than a GitLab/Gitea CI/CD server (a hypervisor, storage appliance, backup product, database, network gear, or OT/industrial equipment) — route those to the appropriate other AIops-tools skill. Do NOT use for Kubernetes deploy state — use k8s-aiops. GitLab.com / Gitea Cloud SaaS accounts are out of scope: this tool targets self-managed instances. Governed CI/CD operations with a built-in governance harness (audit, policy, token budget, undo, risk-tiers).

ClawHub Claude Code author: wei zhou v0.10.2 MIT-0 6 files body ≈ 2 997 tokens Open the sourceclawhub.ai↗ analyzed 7 min ago

Use this skill whenever the user needs to operate a self-managed GitLab or self-hosted Gitea CI/CD server — a one-shot overview, server version and token…

As a process B 72/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureGitLabKubernetesAI and agentstype 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
B
84/100
safety, quality, tests
Safety 60%
95
Quality 40%
67
Run on models
none yet
Process rating
B
72/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. Shorten the description to 1024 characters.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Bash

Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error description-long description is 1416 chars, limit 1024
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "installer"

Process rating: all ten parameters 72/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 13 mutating operations with no state check
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 39 steps
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2997 tokens
  • 100Progress reporting. Reports progress
  • low The response is described with custom markup (4 tags): a typed call is more reliable

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

  • +3Description length 1415: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +5Description quotes 13 example trigger phrases
  • +4Description says when NOT to use the skill
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 39 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: suspicious
This CI/CD management skill is purpose-aligned, but it needs Review because it installs unpinned external code and can make high-impact GitLab/Gitea changes with limited built-in authorization controls.
LLM: suspicious (high) · 12 Sept 2026