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.
Alibaba Cloud Cloud Firewall ACL rule read-only diagnostic assistant.
As a process B 76/100 · Nearly there — weak spots: running it twice
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
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.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
How to improve
- 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
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medium Broad scope
meta-broad-allowed-toolsSKILL.md:1Broad tool permissions pre-approved: Bashallowed-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.