SKILLEMALL.ai

AF huawei-cloud-ucs-policy-governor

Huawei Cloud UCS (Ubiquitous Cloud Native Service) policy governance and compliance management skill using hcloud CLI. Use this skill when the user wants to: (1) manage UCS policy instances - create/update/query/delete, (2) manage UCS policy definitions - query/list, (3) enable/disable policies on clusters or fleet groups, (4) check policy enforcement job status, (5) audit fleet compliance and review policy enforcement status. Trigger: user mentions "UCS policy", "UCS 策略", "UCS governance", "UCS 治理", "UCS compliance", "UCS 合规", "policy instance", "策略实例", "policy definition", "策略定义", "enable policy", "启用策略", "disable policy", "禁用策略", "fleet compliance", "舰队合规", "policy audit", "策略审计", "UCS 策略管理", "UCS 合规治理", "policy governance", "策略治理"

ClawHub Agent Skills author: huaweicloud-skills-team v1.0.2 MIT-0 10 files body ≈ 5 964 tokens Open the sourceclawhub.ai analyzed 3 d ago

Huawei Cloud UCS (Ubiquitous Cloud Native Service) policy governance and compliance management skill using hcloud CLI.

As a process F 65/100 · Will not run — References files that are not bundled: verification-method.md

ProcedureKubernetesSecuritytype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
F
65/100
Will not run
References files that are not bundled: verification-method.md
Tools and files w 18
0
Progress reporting w 2
0
Running it twice w 4
30
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.
  2. 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 · 0

✓ No critical or high findings

Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5964 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: verification-method.md
  • note frontmatter-key unknown frontmatter key "id"
  • note frontmatter-key unknown frontmatter key "triggers"

Process rating: all ten parameters 65/100

Will not run. References files that are not bundled: verification-method.md
  • 0Tools and files. 1 referenced file(s) missing: verification-method.md
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 44 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 5964 tokens
  • 85Steps. 81 steps, 1 vague phrases
  • 100Result and completion. Output format and completion criterion are stated
  • 100When it triggers. States when to use and when not to
  • 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 14 top-level sections: this looks like several domains in one skill
  • 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 15 example trigger phrases
  • +3Description length 744: enough signal without eating the budget
  • +4Structure: 29 headings
  • +3Step-by-step instructions: 81 items
  • +3Output format is stated explicitly
  • +4Has examples (9 code blocks)
  • +4Reference files are cited in the instructions (8 of 8)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: suspicious
The skill is mostly a disclosed Huawei Cloud policy-governance guide, but some audit workflows cross into cluster credential retrieval and live resource changes without enough scoping or safeguards.
LLM: suspicious (high) · 4 Aug 2026