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BA huawei-cloud-cce-workload-failure-diagnoser

Huawei Cloud CCE workload failure diagnosis skill using Python SDK dispatcher. Use this skill when the user wants to: (1) diagnose Deployment/StatefulSet/DaemonSet rollout failures, (2) analyze workload replica shortages and update rollback issues, (3) diagnose probe-related readiness failures (startup, liveness, readiness), (4) identify ReplicaSet creation blocked by quota, admission, or webhook rejection, (5) detect control-plane-not-observed issues (observedGeneration lag), (6) check workload status, events and metrics comprehensively. Trigger: user mentions "workload failure", "工作负载故障", "Deployment rollback", "Deployment 回滚", "rollout stuck", "发布失败", "replica unavailable", "副本不可用", "workload diagnosis", "工作负载诊断", "workload unavailable", "负载异常", "Service unreachable", "Service 不通", "probe failure", "探针失败", "ReplicaSet blocked", "ReplicaSet 阻塞", "observedGeneration lag", "控制面未观测"

ClawHub Agent Skills author: shijingcheng v0.1.0 MIT-0 52 files body ≈ 5 887 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Huawei Cloud CCE workload failure diagnosis skill using Python SDK dispatcher.

As a process A 80/100 · Runs to the end — no weak spots found

IntegrationKubernetesInfrastructureData and analyticstype 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
87/100
safety, quality, tests
Safety 60%
93
Quality 40%
79
Run on models
none yet
Process rating
A
80/100
Runs to the end
Tools and files w 18
60
Result and completion w 14
60
Inputs and preconditions w 11
70
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 7

✓ No critical or high findings

Medium and low: 7
  • low Dangerous commands cmd-execpolicy-bypass references/verification-method.md:8
    Runs PowerShell with execution policy bypassed (quoted — discussed, not commanded)
    - Windows: `skill action=exec: powershell -ExecutionPolicy Bypass -File skill://scripts/chec…ps1`
    quoted
  • low Secrets in code secret-high-entropy-token scripts/huawei_cloud/aom.py:665
    High-entropy token-like string (may be an id, hash or a credential)
    AddO…ody,
  • low Secrets in code secret-high-entropy-token scripts/huawei_cloud/aom.py:737
    High-entropy token-like string (may be an id, hash or a credential)
    body = AddO…ody(
  • low Secrets in code secret-high-entropy-token scripts/huawei_cloud/aom.py:932
    High-entropy token-like string (may be an id, hash or a credential)
    Dele…ody,
  • low Secrets in code secret-high-entropy-token scripts/huawei_cloud/aom.py:1336
    High-entropy token-like string (may be an id, hash or a credential)
    AddO…ody,
  • low Secrets in code secret-high-entropy-token scripts/huawei_cloud/aom.py:1372
    High-entropy token-like string (may be an id, hash or a credential)
    body = AddO…ody(
  • low Dangerous commands cmd-execpolicy-bypass SKILL.md:67
    Runs PowerShell with execution policy bypassed (quoted — discussed, not commanded)
    - Windows: `skill action=exec: powershell -ExecutionPolicy Bypass -File skill://scripts/chec…ps1`
    quoted

Files scanned: 12. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5887 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "id"

Process rating: all ten parameters 80/100

  • 60Tools and files. Uses tools (bash, web, python, node) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 5887 tokens
  • 85Steps. 63 steps, 2 vague phrases
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 2 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 10 top-level sections: this looks like several domains in one skill

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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 894: 120–800 characters recommended
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 16 example trigger phrases
  • +4Structure: 27 headings
  • +3Step-by-step instructions: 63 items
  • +3Output format is stated explicitly
  • +4Has examples (10 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

External checks

ClawHub: suspicious
The skill is described as a read-only Huawei CCE workload diagnoser, but the packaged dispatcher exposes powerful cloud, cluster, credential, secret, and remediation actions beyond that purpose.
LLM: suspicious (high) · VirusTotal: · 17 Jun 2026