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BC huawei-cloud-cce-cost-optimization-advisor

Huawei Cloud CCE cost optimization analysis skill. Identifies idle resources, oversized CPU/memory requests, low-utilization nodes, 24h/7d utilization trends, HPA recommendations, and node autoscaler policy optimization. Read-only analysis and configuration suggestions only — does not modify HPA, autoscaler, node pools, or workloads without explicit user confirmation. Trigger: user mentions "cost optimization", "成本优化", "cost advisor", "成本顾问", "resource waste", "资源浪费", "cost reduction", "成本降低", "billing analysis", "账单分析", "over-provisioned", "超配", "CCE cost", "idle nodes", "oversized request", "HPA recommendation", "autoscaler policy"

ClawHub Agent Skills author: shijingcheng v0.1.1 MIT-0 52 files · 44 scripts body ≈ 4 835 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

Huawei Cloud CCE cost optimization analysis skill.

As a process C 52/100 · Has gaps — References files that are not bundled: references/verification-method.md

AnalyzerKubernetesData 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
91/100
safety, quality, tests
Safety 60%
93
Quality 40%
87
Run on models
none yet
Process rating
C
52/100
Has gaps
References files that are not bundled: references/verification-method.md
Tools and files w 18
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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 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 Secrets in code secret-password-literal scripts/huawei_cloud/cce_node.py:646
    Hard-coded password / key literal (may be an example)
    login = Login(user_password=UserPassword(username="root", password=salted_b64))
  • low Secrets in code secret-password-literal scripts/huawei_cloud/cce_nodepool.py:456
    Hard-coded password / key literal (may be an example)
    user_password.password = base…ode(hashed.encode("utf-8")).decode("utf-8")

Files scanned: 52. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/verification-method.md

Process rating: all ten parameters 52/100

Will not run. References files that are not bundled: references/verification-method.md
  • 0Tools and files. 1 referenced file(s) missing: references/verification-method.md
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 12 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 4835 tokens
  • 100Steps. 54 steps
  • 100Consistency. Name and required fields are in place
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 16 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)
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 11 example trigger phrases
  • +3Description length 641: enough signal without eating the budget
  • +4Structure: 37 headings
  • +3Step-by-step instructions: 54 items
  • +3Output format is stated explicitly
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

External checks

ClawHub: suspicious
This skill is advertised as a read-only Huawei CCE cost advisor, but it ships callable cloud and Kubernetes admin actions that can modify infrastructure and access secrets or logs.
LLM: suspicious (high) · 16 Jun 2026