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BB huawei-cloud-cce-list

Query the list of Huawei Cloud CCE (Cloud Container Engine) clusters under the current tenant / project, focused on the CCE cluster NAME list. Returns each cluster's name, id, status (phase), version and flavor. Supports filtering by status and cluster type, and extracting a pure cluster-name list. Uses the KooCLI command `hcloud CCE ListClusters --cli-region={region}` (primary) against the v3 API, or the huaweicloudsdkcce Python SDK (fallback). Read-only — never creates, modifies or deletes any cluster or node. Use this skill whenever the user wants to list/inspect the CCE clusters of the tenant or query the CCE cluster name list, e.g. for CCE cluster inventory, daily inspection, or cost review. Triggers include: "list CCE clusters", "CCE cluster list", "query CCE cluster names", "CCE name list", "CCE集群列表", "查询CCE集群", "CCE集群名称列表", "CCE集群名称", "list cce", "cce list", "how many CCE clusters".

ClawHub Agent Skills author: huaweiclouddev-dev v1.0.2 MIT-0 30 files · 2 scripts body ≈ 1 338 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

Query the list of Huawei Cloud CCE (Cloud Container Engine) clusters under the current tenant / project, focused on the CCE cluster NAME list.

As a process B 70/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting

ProcedureSoftware developmentCommercetype 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
88/100
safety, quality, tests
Safety 60%
89
Quality 40%
87
Run on models
none yet
Process rating
B
70/100
Nearly there
Progress reporting w 2
0
Running it twice w 4
30
Result and completion w 14
40
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.

Dangerous commands 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 skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

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 · 3

    ✓ No critical or high findings

    Medium and low: 3
    • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:12
      Privilege escalation / world-writable permissions
      sudo mv hcloud /usr/local/bin/
    • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:18
      Privilege escalation / world-writable permissions
      sudo mv hcloud /usr/local/bin/
    • low Risky intent intent-offensive-security references/skill-gate-report.txt:21
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      Result: PASS — no eval/exec/system shell=True, reverse shell, or pipe-to-sh patterns.

    Files scanned: 30. 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 70/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 1 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 22 steps, 1 vague phrases
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1338 tokens
    • low The response is described with custom markup (4 tags): a typed call is more reliable

    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 903: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • -32 of 2 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 10 example trigger phrases
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 22 items
    • +4Has examples (8 code blocks)
    • +4Reference files are cited in the instructions (5 of 6)

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

    External checks

    ClawHub: suspicious
    The skill is read-only, but its documents conflict about whether it may collect node and addon details from CCE clusters.
    LLM: suspicious (high) · 2 Sept 2026