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AB huawei-cloud-cce-chaos-experiment

Huawei Cloud CCE AZ power outage chaos experiment — end-to-end fault drill: discover clusters and node AZ distribution, validate cross-AZ capacity, shut down all CCE nodes in one AZ to simulate a power failure, observe Pod eviction and rescheduling to surviving AZs, then start nodes back and verify recovery, and optionally analyze logs for an impact report. Use this skill when the user wants to run or prepare a CCE fault drill / chaos experiment / AZ outage drill. Triggers: CCE, 故障演练, 混沌演练, AZ断电, 演练, 故障注入, chaos experiment, AZ power outage, fault drill, chaos drill.

ClawHub Agent Skills author: huaweicloudskill v1.0.0 MIT-0 26 files · 13 scripts body ≈ 3 491 tokens Open the sourceclawhub.ai↗ analyzed 5 d ago

Huawei Cloud CCE AZ power outage chaos experiment — end-to-end fault drill: discover clusters and node AZ distribution, validate cross-AZ capacity, shut down…

As a process B 67/100 · Nearly there — weak spots: result and completion, running it twice

AnalyzerKubernetesData and analyticsInfrastructuretype 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
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
B
67/100
Nearly there
Result and completion w 14
0
Running it twice w 4
30
Failures and branches w 10
50
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: 26. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "triggers"

    Process rating: all ten parameters 67/100

    • 0Result and completion. Does not say what the result is
    • 30Running it twice. 11 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (web, python, node) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 53 steps
    • 100Inputs and preconditions. Inputs and preconditions are listed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3491 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

    • +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
    • +1No license
    • +2Single-language instructions
    • +3Description length 572: enough signal without eating the budget
    • +4Structure: 35 headings
    • +3Step-by-step instructions: 53 items
    • +4Has examples (21 code blocks)
    • +4Reference files are cited in the instructions (7 of 11)
    • +3All 13 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

    External checks

    ClawHub: suspicious
    This appears to be a real Huawei CCE chaos-drill skill, but it needs Review because it can stop cloud cluster nodes and its executor does not enforce the documented confirmation and validation gates.
    LLM: suspicious (high) · 30 Sept 2026