SKILLEMALL.ai

AB alibabacloud-waf-rule-effectiveness-check

Diagnose why a configured Alibaba Cloud WAF 3.0 custom protection rule (custom ACL, CC / rate limiting, scan protection, IP blacklist) is not working: name the first broken link in the chain and hand back the console fix path. Read-only checks of configuration state only; never sends test traffic. Use it when a customer says a rule has no effect at all, a rule matches in the logs but nothing is blocked, an attack that should have been blocked got through, a rule worked yesterday but not today, or a CC or rate-limiting rule does not trigger or bans far too widely. Not for: explaining why one specific request was blocked or looking it up by trace_id, whitelist rule effectiveness itself, live attack sample validation, built-in rule toggles, config export, or reports. Triggers: "规则不生效", "规则配了但不生效", "自定义规则不生效", "预期拦未拦", "该拦的没拦住", "漏拦截", "规则命中但没拦", "规则昨天还好今天失效", "CC不触发", "误封面过大", "规则为什么没生效", "WAF rule not effective", "rule not taking effect", "rule hit but not blocked"

ClawHub Agent Skills author: alibabacloud-skills-team v0.0.1 MIT-0 13 files body ≈ 8 040 tokens Open the sourceclawhub.ai analyzed 3 d ago

Diagnose why a configured Alibaba Cloud WAF 3.0 custom protection rule (custom ACL, CC / rate limiting, scan protection, IP blacklist) is not working: name…

As a process B 74/100 · Nearly there — weak spots: result and completion, execution cost

AnalyzerInfrastructureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
97
Quality 40%
87
Run on models
none yet
Process rating
B
74/100
Nearly there
Result and completion w 14
40
Execution cost w 6
40
Failures and branches w 10
50
the three weakest of ten parameters · all ten

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 · 3

✓ No critical or high findings

Medium and low: 3
  • low Dangerous commands cmd-privilege references/cli-installation-guide.md:19
    Privilege escalation / world-writable permissions (documentation of a security skill)
    sudo mv aliyun /usr/local/bin/
    security skill
  • low Dangerous commands cmd-privilege references/cli-installation-guide.md:27
    Privilege escalation / world-writable permissions (documentation of a security skill)
    sudo mv aliyun /usr/local/bin/
    security skill

A further 1 matches are quotations in this security skill's documentation and are not counted as findings.

Files scanned: 13. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 8040 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 74/100

  • 40Result and completion. Does not say what the result is
  • 40Execution cost. Instruction body is 8040 tokens: crowds the task out of the window
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 85Steps. 47 steps, 1 vague phrases
  • 100When it triggers. States when to use and when not to
  • 100Inputs and preconditions. Inputs and preconditions are listed
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 17 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

  • +3Description length 977: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 9 example trigger phrases
  • +4Description says when NOT to use the skill
  • +4Structure: 26 headings
  • +3Step-by-step instructions: 47 items
  • +4Has examples (10 code blocks)
  • +4Reference files are cited in the instructions (9 of 9)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

External checks

ClawHub: suspicious
The skill’s core WAF diagnosis is read-only, but its setup guidance is broader and riskier than the stated WAF-only purpose.
LLM: suspicious (high) · 24 Aug 2026