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BC alibabacloud-network-ga-deploy-acceleration

Deploy acceleration services using Alibaba Cloud Global Accelerator (GA). Applicable to cross-border Web/API acceleration, global gaming acceleration, audio/video transmission acceleration, and more. Trigger words: "GA acceleration", "Global Accelerator", "deploy GA", "create GA instance", "GA", "acceleration configuration"

ClawHub Agent Skills author: alibabacloud-skills-team v0.0.1-beta.1 MIT-0 8 files body ≈ 6 223 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 59/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice

IntegrationInfrastructuretype 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%
80
Quality 40%
86
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
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

  1. 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 · 4

✓ No critical or high findings

Medium and low: 4
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:30
    Privilege escalation / world-writable permissions
    sudo mv aliyun /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:45
    Privilege escalation / world-writable permissions
    sudo mv aliyun /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:58
    Privilege escalation / world-writable permissions
    sudo mv aliyun /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:71
    Privilege escalation / world-writable permissions
    sudo mv aliyun /usr/local/bin/

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

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6223 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 59/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 15 mutating operations with no state check
  • 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 6223 tokens
  • 100Steps. 22 steps
  • 100Failures and branches. 5 branches, has a failure section
  • 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 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 5 example trigger phrases
  • +3Description length 325: enough signal without eating the budget
  • +4Structure: 23 headings
  • +3Step-by-step instructions: 22 items
  • +4Has examples (11 code blocks)
  • +4Reference files are cited in the instructions (5 of 5)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

External checks

ClawHub: suspicious
The skill matches its Alibaba Cloud GA deployment purpose, but it needs Review because it can create or delete paid cloud network resources and includes under-scoped credential and cleanup guidance.
LLM: suspicious (high) · VirusTotal: · 29 May 2026