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AC alibabacloud-cms-alert-rule-create

Create and query Alibaba Cloud alert rules via CLI. Supports CMS 1.0 cloud resource monitoring (ECS, RDS, SLB, etc.) and CMS 2.0 advanced monitoring (Prometheus, APM, UModel). Intent routing automatically selects the correct workflow based on alert type. Use this skill when users mention: create alert, setup monitoring, configure alarm, ECS/RDS/SLB alert, Prometheus alert, PromQL, K8s monitoring, APM alert, UModel alert, list alerts, query rules, 告警规则, 创建告警, 监控报警, Prometheus告警, 应用监控, 查看告警.

ClawHub Agent Skills author: alibabacloud-skills-team v0.0.2 MIT-0 21 files · 1 script body ≈ 1 805 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 64/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

IntegrationKubernetesInfrastructuretype 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
93/100
safety, quality, tests
Safety 60%
99
Quality 40%
85
Run on models
none yet
Process rating
C
64/100
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Secrets in code secret-high-entropy-token references/metrics.md:290
      High-entropy token-like string (may be an id, hash or a credential)
      | Proc…nV2 | 进程内存利用率 | % | Average | > 80% |

    Files scanned: 21. 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 64/100

    • 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. 10 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 100Tools and files. No external tools needed
    • 100Steps. 15 steps
    • 100Failures and branches. 4 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1805 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 496: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 15 items
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (18 of 18)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: suspicious
    The skill is mostly aligned with Alibaba Cloud alert management, but it also exposes disabling, deleting, and updating alert rules without enough safeguards.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026