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BC ci-monitor

Monitor and interact with CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI). Check build status, trigger builds, analyze failed jobs, view logs. Use when: (1) checking build/pipeline status, (2) triggering test builds, (3) analyzing CI failures, (4) monitoring deployment status, (5) "查看构建状态", "Jenkins", "流水线", "CI失败了", "触发构建". Requires: curl for API calls. Jenkins needs JENKINS_URL and JENKINS_TOKEN env vars. NOT for: configuring CI pipelines (edit Jenkinsfile/yaml directly), or managing infrastructure.

ClawHub Agent Skills author: zhanghengyi1986-afk v1.0.0 MIT-0 2 files body ≈ 1 013 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 61/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

IntegrationGitHubGitLabInfrastructuretype 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
85/100
safety, quality, tests
Safety 60%
80
Quality 40%
93
Run on models
none yet
Process rating
C
61/100
Has gaps
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.

Exfiltration 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 instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

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 · 4

    ✓ No critical or high findings

    Medium and low: 4
    • medium Exfiltration net-credential-use SKILL.md:140
      Credential used in a network call (verify the destination is the intended service)
      curl -s -H "PRIVATE-TOKEN: $GITLAB_TOKEN" \
    • medium Exfiltration net-credential-use SKILL.md:144
      Credential used in a network call (verify the destination is the intended service)
      curl -s -H "PRIVATE-TOKEN: $GITLAB_TOKEN" \
    • medium Exfiltration net-credential-use SKILL.md:148
      Credential used in a network call (verify the destination is the intended service)
      curl -s -H "PRIVATE-TOKEN: $GITLAB_TOKEN" \
    • medium Exfiltration net-credential-use SKILL.md:152
      Credential used in a network call (verify the destination is the intended service)
      curl -s -X POST -H "PRIVATE-TOKEN: $GITLAB_TOKEN" \

    Files scanned: 2. 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 61/100

    • 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. 1 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 100Tools and files. No external tools needed
    • 100Steps. 12 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1013 tokens
    • 100Progress reporting. Reports progress

    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

    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 2 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 511: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 12 items
    • +4Has examples (9 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.

    External checks

    ClawHub: clean
    This is a disclosed CI/CD helper with expected token and build-control examples, but users should treat its commands as real operational actions.
    LLM: benign (high) · VirusTotal: · 29 May 2026