SKILLEMALL.ai

CF huawei-cloud-cce-env-assessment

A skill for huawei cloud container(CCE) assessment. It automatically collects metrics and configurations from containerized application environments on Huawei Cloud to generate a comprehensive assessment report. Use this when users want to evaluate if their Huawei Cloud applications align with cloud-native best practices and identify areas for improvement.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: huaweiclouddev-dev v1.0.1 MIT-0 11 files body ≈ 3 206 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 73/100 · Will not run — References files that are not bundled: references/cloud-native-checklist.xlsx

AnalyzerData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
C
67/100
safety, quality, tests
Safety 60%
57
Quality 40%
81
Run on models
none yet
Process rating
F
73/100
Will not run
References files that are not bundled: references/cloud-native-checklist.xlsx
Tools and files w 18
0
Progress reporting w 2
0
When it triggers w 12
70
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: ClawHub

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
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

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  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 · 6

  • high Dangerous commands cmd-destructive-fs scripts/collect_all.py:312
    Destructive filesystem command (wipes root/home/drive) (string literal in code, not executed)
    8: "读取业务源码仓库的 Dockerfile,检查是否包含 rm -rf / apt-get clean 等清理指令",
    code literal
Medium and low: 5
  • medium Dangerous commands cmd-privilege references/koocli-installation-guide.md:49
    Privilege escalation / world-writable permissions
    sudo mv hcloud /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/koocli-installation-guide.md:54
    Privilege escalation / world-writable permissions
    sudo mv hcloud /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/koocli-installation-guide.md:73
    Privilege escalation / world-writable permissions
    sudo mv hcloud /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/koocli-installation-guide.md:78
    Privilege escalation / world-writable permissions
    sudo mv hcloud /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/koocli-installation-guide.md:157
    Privilege escalation / world-writable permissions
    sudo bash ./hcloud_install.sh

Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/cloud-native-checklist.xlsx
  • note frontmatter-key unknown frontmatter key "Triggers"

Process rating: all ten parameters 73/100

Will not run. References files that are not bundled: references/cloud-native-checklist.xlsx
  • 0Tools and files. 1 referenced file(s) missing: references/cloud-native-checklist.xlsx
  • 0Progress reporting. Says nothing while it works
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 67 steps
  • 100Result and completion. Output format and completion criterion are stated
  • 100Failures and branches. 8 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3206 tokens
  • 100Running it twice. Mutating operations check current state
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 13 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

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • -31 of 5 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 360: enough signal without eating the budget
  • +4Structure: 34 headings
  • +3Step-by-step instructions: 67 items
  • +3Output format is stated explicitly
  • +4Has examples (6 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: suspicious
The skill is mostly an assessment tool, but it asks for powerful cloud credentials and can run broad local and cloud actions without tight scoping.
LLM: suspicious (high) · 5 Aug 2026