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BC huawei-cloud-apig-instance-management

Manage Huawei Cloud APIG (API Gateway, dedicated instances) via hcloud CLI: instance lifecycle (create/list/delete), API groups, API create/update/delete, publish/offline, request throttling policies, and public ingress EIP binding, plus read-only diagnosis of public access (eip_address vs sl_domain) and the instance -> group -> API -> publish chain. Delete operations require explicit user confirmation; instance creation is a 5-15 minute async operation that must be polled until status == Running. Triggers include: APIG, API gateway, 网关, API 分组, API 管理, 流控策略, throttling, publish API, 发布 API, 下线 API, 实例管理, 公网访问, ingress EIP, API 网关排障, apig.

ClawHub Agent Skills author: huaweicloud-skills-team v1.0.0 MIT-0 8 files body ≈ 5 247 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

Manage Huawei Cloud APIG (API Gateway, dedicated instances) via hcloud CLI: instance lifecycle (create/list/delete), API groups, API create/update/delete…

As a process C 58/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice

IntegrationPeople and hiringtype 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
82/100
safety, quality, tests
Safety 60%
95
Quality 40%
63
Run on models
none yet
Process rating
C
58/100
Has gaps
Progress reporting w 2
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. 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 · 5

✓ No critical or high findings

Medium and low: 5
  • low Secrets in code secret-high-entropy-token references/acceptance-criteria.md:35
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    `Crea…yV2`, `List…yV2`
    quoted
  • low Secrets in code secret-high-entropy-token references/verification-method.md:38
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition; documentation table row)
    | `huawei_create_apig_throttling_policy` | `List…yV2 --instance_id` contains the new policy |
    detectortable
  • low Secrets in code secret-high-entropy-token SKILL.md:54
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition; documentation table row)
    | 7 | API / throttling policy names must NOT have hyphens | `[a-zA-Z0-9_]+` only. Hyphens cause regex validation failure (verified for `Crea…yV2` too, APIG.2011). |
    detectortable
  • low Secrets in code secret-high-entropy-token SKILL.md:157
    High-entropy token-like string (may be an id, hash or a credential)
    hcloud APIG List…yV2 --cli-region={region} --instance_id={instance_id} --limit=20
  • low Secrets in code secret-high-entropy-token SKILL.md:344
    High-entropy token-like string (may be an id, hash or a credential)
    hcloud APIG Crea…yV2 --cli-region={region} --instance_id={instance_id} --name={name} --time_unit={time_unit} --time_interval={time_interval} --api_call_limits={api_call_limits}

Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 5247 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 58/100

  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 51 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 5247 tokens
  • 85Steps. 13 steps, 1 vague phrases
  • 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
  • high The skill tells the model to perform an irreversible action with no human approval
  • low The response is described with custom markup (5 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

  • +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 647: enough signal without eating the budget
  • +4Structure: 25 headings
  • +3Step-by-step instructions: 13 items
  • +4Has examples (19 code blocks)
  • +4Reference files are cited in the instructions (5 of 5)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.

External checks

ClawHub: suspicious
This APIG management skill is mostly coherent, but it bundles an undisclosed telemetry SDK that can send IAM-authenticated execution data off-box and its setup guidance relies on mutable installers.
LLM: suspicious (high) · 11 Sept 2026