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CC alibabacloud-oss-manage-metaquery

Alicloud OSS AI Content Awareness Skill. Use for enabling and querying OSS semantic search with AI-powered content understanding. Triggers: "OSS AI Content Awareness", "OSS semantic search", "OSS vector search", "search by text", "text-to-image search", "text-to-video search", "OSS MetaQuery", "OSS data index", "OSS AI内容感知", "OSS语义检索", "OSS向量检索", "以文搜图", "以文搜视频", "OSS数据索引"

ClawHub Agent Skills author: alibabacloud-skills-team v0.0.2 MIT-0 18 files body ≈ 5 319 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 62/100 · Has gaps — weak spots: result and completion, when it triggers, progress reporting

ProcedureInfrastructureMedia and videotype 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
C
73/100
safety, quality, tests
Safety 60%
69
Quality 40%
80
Run on models
none yet
Process rating
C
62/100
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 · 7

✓ No critical or high findings

Medium and low: 7
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:39
    Privilege escalation / world-writable permissions
    sudo mv aliyun /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:50
    Privilege escalation / world-writable permissions
    sudo mv aliyun /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:60
    Privilege escalation / world-writable permissions
    sudo mv aliyun /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:70
    Privilege escalation / world-writable permissions
    sudo mv aliyun /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/ossutil-installation-guide.md:48
    Privilege escalation / world-writable permissions
    sudo mv ossutil /usr/local/bin/
  • medium Dangerous commands cmd-pipe-to-shell SKILL.md:20
    Downloads and executes remote code from an unrecognised host (pipe to shell) (quoted — discussed, not commanded)
    > run `curl -fsSL https://aliyuncli.alicdn.com/setup.sh | bash` to install/update,
    quoted
  • low Secrets in code secret-high-entropy-token references/metaquery.md:142
    High-entropy token-like string (may be an id, hash or a credential)
    Query results contain rich field information. For detailed descriptions, refer to the official documentation: [DoMetaQuery Response Field Descriptions](https://help.aliyun.com/zh/oss/developer-referen

Files scanned: 18. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5319 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 62/100

  • 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
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 5319 tokens
  • 100Steps. 45 steps
  • 100Failures and branches. 12 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 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 The response is described with custom markup (18 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
  • -38 of 9 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 12 example trigger phrases
  • +3Description length 375: enough signal without eating the budget
  • +4Structure: 26 headings
  • +3Step-by-step instructions: 45 items
  • +4Has examples (23 code blocks)
  • +4Reference files are cited in the instructions (5 of 7)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

External checks

ClawHub: clean
This is a disclosed Alibaba Cloud OSS semantic-search management skill, but it can affect real cloud buckets and should be used with scoped credentials and careful confirmations.
LLM: benign (high) · VirusTotal: · 29 May 2026