SKILLEMALL.ai

BC alibabacloud-cas-ssl-cert-deploy

Deploy SSL certificates to Alibaba Cloud products (CDN/SLB/WAF/ALB/NLB/OSS/ESA, etc.). One-click or batch deployment via CAS DeploymentJob API, with progress tracking, failure diagnosis, rollback, and HTTPS verification. Activate when user says "deploy certificate to CDN", "deploy to SLB", "one-click deploy certificate", "push certificate to cloud", "部署证书到 CDN", "部署到 SLB", "一键部署证书", "证书推送到云产品".

ClawHub Agent Skills author: alibabacloud-skills-team v0.0.1 MIT-0 10 files body ≈ 10 291 tokens Open the sourceclawhub.ai analyzed 2 d ago

Deploy SSL certificates to Alibaba Cloud products (CDN/SLB/WAF/ALB/NLB/OSS/ESA, etc.). One-click or batch deployment via CAS DeploymentJob API, with progress…

As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions, execution cost

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
90
Quality 40%
81
Run on models
none yet
Process rating
C
55/100
Has gaps
Inputs and preconditions w 11
0
Running it twice w 4
30
Result and completion w 14
40
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 · 2

✓ No critical or high findings

Medium and low: 2
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:42
    Privilege escalation / world-writable permissions
    sudo mv aliyun /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:48
    Privilege escalation / world-writable permissions
    sudo mv aliyun /usr/local/bin/

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

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 10291 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 55/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 142 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 40Execution cost. Instruction body is 10291 tokens: crowds the task out of the window
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
  • 60Steps. 30 steps, 4 vague phrases
  • 100Failures and branches. 7 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 14 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
  • -233 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 8 example trigger phrases
  • +3Description length 397: enough signal without eating the budget
  • +4Structure: 40 headings
  • +3Step-by-step instructions: 30 items
  • +4Has examples (17 code blocks)
  • +4Reference files are cited in the instructions (8 of 8)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: suspicious
The skill is aimed at certificate deployment, but it also grants and documents broad cloud-provisioning and credential-handling authority that needs careful review before use.
LLM: suspicious (high) · 31 Jul 2026