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BC alibabacloud-pai-quota-management

End-to-end Alibaba Cloud PAI Quota lifecycle management via `aliyun paistudio` (Quota CRUD, scale, workload inspection) and `aliyun aiworkspace` (binding Quotas to Workspaces). Covers root and child quota creation, absolute scaling, metadata update, deletion, listing quota workloads / active user usages, plus attaching and detaching quotas to PAI workspaces. Use when the user asks to list / get / create / update / scale / delete PAI quotas, inspect quota workloads or active users, or attach / detach quotas to a workspace. Trigger phrases: "PAI quota", "create PAI quota", "scale PAI quota", "child quota", "quota tree", "bind quota to workspace", "list PAI quotas", "Lingjun quota", "PAI 资源配额", "Quota 扩缩容".

ClawHub Agent Skills author: alibabacloud-skills-team v0.0.1 MIT-0 9 files body ≈ 5 562 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

End-to-end Alibaba Cloud PAI Quota lifecycle management via aliyun paistudio (Quota CRUD, scale, workload inspection) and aliyun aiworkspace (binding Quotas…

As a process C 61/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureSales and CRMtype 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
87/100
safety, quality, tests
Safety 60%
95
Quality 40%
76
Run on models
none yet
Process rating
C
61/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:22
    Privilege escalation / world-writable permissions
    sudo mv aliyun /usr/local/bin/aliyun

Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5562 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "domain"
  • note frontmatter-key unknown frontmatter key "required_permissions"

Process rating: all ten parameters 61/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 68 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 60Failures and branches. 2 branches
  • 70Execution cost. Instruction body is 5562 tokens
  • 85Steps. 6 steps, 3 vague phrases
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • low 10 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (22 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)
  • +3Output format is not stated: the model decides each time
  • -5TODO / placeholder text left in the skill
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 10 example trigger phrases
  • +3Description length 713: enough signal without eating the budget
  • +4Structure: 25 headings
  • +3Step-by-step instructions: 6 items
  • +4Has examples (12 code blocks)
  • +4Reference files are cited in the instructions (7 of 7)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: clean
This skill is a disclosed Alibaba Cloud PAI quota-management helper with high-impact cloud permissions, but its risky actions are purpose-aligned and gated by confirmation workflows.
LLM: benign (medium) · VirusTotal: · 10 Jun 2026