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AF alibabacloud-milvus-manage

Alibaba Cloud Milvus full-stack Skill for two planes: control-plane instance management via aliyun CLI, and data-plane Milvus operations via pymilvus. Use when users want to create, inspect, scale, configure, network-enable, or whitelist Alibaba Cloud Milvus instances; or connect to Milvus and perform collection management, vector insert/search, hybrid search, full-text search, index management, partition/database management, or RBAC with Python.

ClawHub Agent Skills author: alibabacloud-skills-team v0.0.3 MIT-0 15 files body ≈ 2 855 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 60/100 · Will not run — References files that are not bundled: references/*.md

IntegrationSoftware developmentInfrastructuretype 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
A
91/100
safety, quality, tests
Safety 60%
94
Quality 40%
86
Run on models
none yet
Process rating
F
60/100
Will not run
References files that are not bundled: references/*.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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope 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 asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. 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 · 2

✓ No critical or high findings

Medium and low: 2
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Bash Read Write
  • low Secrets in code secret-password-literal references/user-role.md:7
    Hard-coded password / key literal (may be an example)
    client.create_user(user_name="analyst", password="SecureP@ss123")

Files scanned: 15. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/*.md

Process rating: all ten parameters 60/100

Will not run. References files that are not bundled: references/*.md
  • 0Tools and files. 1 referenced file(s) missing: references/*.md
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 25 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 104 steps, 1 vague phrases
  • 100Failures and branches. 4 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2855 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • high The skill tells the model to perform an irreversible action with no human approval

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)
  • +2Single-language instructions
  • +3Description length 450: enough signal without eating the budget
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 104 items
  • +3Output format is stated explicitly
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (13 of 13)
  • +1License stated

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

External checks

ClawHub: suspicious
This is a coherent Milvus management skill, but it can make real cloud, network, credential, and access-control changes with safety guidance that is too thin in several places.
LLM: suspicious (high) · VirusTotal: · 29 May 2026