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BB alibabacloud-mcp-connector

Operate, run O&M for, and manage Alibaba Cloud through local commands, with no MCP configuration needed. CallCLI runs Alibaba Cloud CLI/API commands to create, read, update and delete resources of any product; RunScript runs Python batch scripts; RunIaC runs Terraform orchestration; plus API retrieval and official-document retrieval to follow the best-practice path. Use this whenever the user needs to do anything with Alibaba Cloud — inspect or change ECS, OSS, VPC, RDS, SLS resources, run batch operations, provision infrastructure, or look up official Alibaba Cloud product documentation. Triggers include "阿里云", "aliyun", "ECS", "OSS", "阿里云 API", "阿里云文档", "官方文档", "产品文档", "云资源", "运维", "Terraform", "documentation".

ClawHub Agent Skills author: alibabacloud-skills-team v1.0.0 MIT-0 10 files body ≈ 7 845 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Operate, run O&M for, and manage Alibaba Cloud through local commands, with no MCP configuration needed.

As a process B 74/100 · Nearly there — weak spots: result and completion, running it twice

ProcedureTerraformInfrastructureAI and agentsSoftware developmenttype 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%
92
Quality 40%
79
Run on models
none yet
Process rating
B
74/100
Nearly there
Result and completion w 14
0
Running it twice w 4
30
Tools and files w 18
60
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-pipe-to-shell-known-host SKILL.md:139
    Pipe-to-shell installer from a well-known host (still executes remote code)
    curl -LsSf https://astral.sh/uv/install.sh | sh
  • low Secrets in code secret-high-entropy-token references/tool-reference.md:83
    High-entropy token-like string (may be an id, hash or a credential)
    3. Call Open…ion tool with the selected API information to get the complete API definition
  • low Dangerous commands cmd-pipe-to-shell-known-host scripts/mcpx.py:46
    Pipe-to-shell installer from a well-known host (still executes remote code) (string literal in code, not executed)
    UV_INSTALL_HINT_POSIX = "curl -LsSf https://astral.sh/uv/install.sh | sh"
    code literal
  • low Dangerous commands cmd-execpolicy-bypass scripts/mcpx.py:48
    Runs PowerShell with execution policy bypassed (quoted — discussed, not commanded)
    'powershell -ExecutionPolicy ByPass -c '
    quoted

Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 7845 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "triggers"

Process rating: all ten parameters 74/100

  • 0Result and completion. Does not say what the result is
  • 30Running it twice. 10 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 70Execution cost. Instruction body is 7845 tokens
  • 100Steps. 51 steps
  • 100When it triggers. States when to use and when not to
  • 100Inputs and preconditions. Inputs and preconditions are listed
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 16 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (3 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
  • -32 of 3 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 4 example trigger phrases
  • +3Description length 722: enough signal without eating the budget
  • +4Structure: 31 headings
  • +3Step-by-step instructions: 51 items
  • +4Has examples (24 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

External checks

ClawHub: suspicious
This is a coherent Alibaba Cloud management skill, but it needs Review because it combines broad cloud-changing authority with unverified remote installers and dependency execution.
LLM: suspicious (high) · VirusTotal: · 9 Sept 2026