SKILLEMALL.ai

AB alibabacloud-cfw-acl-diagnosis

Alibaba Cloud Cloud Firewall ACL rule read-only diagnostic assistant. **Trigger Scenarios**: Diagnose ACL rules not taking effect, troubleshoot Internet/NAT/VPC firewall traffic issues, query traffic logs, check matched rules, get configuration guidance (console manual operation). **Supported firewall types**: Internet Firewall, NAT Boundary Firewall, VPC Boundary Firewall **Keywords**: Cloud Firewall rules not taking effect, Internet Firewall ACL diagnosis, NAT Firewall policy not working, VPC Boundary Firewall rule diagnosis, firewall rule diagnosis ⚠️ **DO NOT use** for WAF issues - use alibabacloud-waf-rule-management skill instead. TEXT-ONLY console guidance. Queries and diagnosis only, no configuration changes.

ClawHub Agent Skills author: alibabacloud-skills-team v0.0.1 MIT-0 10 files body ≈ 3 079 tokens Open the sourceclawhub.ai analyzed 32 h ago

Alibaba Cloud Cloud Firewall ACL rule read-only diagnostic assistant.

As a process B 76/100 · Nearly there — weak spots: running it twice

AnalyzerAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
95
Quality 40%
94
Run on models
none yet
Process rating
B
76/100
Nearly there
Running it twice w 4
30
When it triggers w 12
50
Result and completion w 14
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.

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

    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 Broad scope meta-broad-allowed-tools SKILL.md:1
      Broad tool permissions pre-approved: Bash
      allowed-tools: Bash Read

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

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 76/100

    • 30Running it twice. 5 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Result and completion. Output format stated, no completion criterion
    • 60Failures and branches. 2 branches
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 54 steps, 1 vague phrases
    • 100Tools and files. Tools declared in frontmatter
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3079 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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
    • -217 emoji in the instructions: noise for the model
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 726: enough signal without eating the budget
    • +4Structure: 19 headings
    • +3Step-by-step instructions: 54 items
    • +3Output format is stated explicitly
    • +4Has examples (5 code blocks)
    • +4Reference files are cited in the instructions (7 of 8)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 94.

    External checks

    ClawHub: clean
    This skill is a disclosed read-only Alibaba Cloud firewall diagnostic helper, but users should understand it can run live cloud queries using their configured credentials.
    LLM: benign (medium) · VirusTotal: · 9 Jul 2026