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AA alibabacloud-waf-rule-management

Alibaba Cloud WAF 3.0 read-only diagnostic assistant for interception diagnosis, rule queries, and configuration guidance. Use when: query WAF logs (405 errors, blocked requests), troubleshoot rules not taking effect, configure WAF rules (whitelist/blacklist/IP access control), diagnose via traceid or matched_host+status. Provides TEXT-ONLY console guidance. Uses `aliyun sls get-logs-v2` (SLS plugin required). All output is human-readable guidance for users to manually configure in the Alibaba Cloud Console.

ClawHub Agent Skills author: alibabacloud-skills-team v0.0.1 MIT-0 12 files body ≈ 4 766 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Alibaba Cloud WAF 3.0 read-only diagnostic assistant for interception diagnosis, rule queries, and configuration guidance. Use when: query WAF logs (405…

As a process A 80/100 · Runs to the end — no weak spots found

AnalyzerAI and agentsInfrastructuretype 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
A
94/100
safety, quality, tests
Safety 60%
95
Quality 40%
93
Run on models
none yet
Process rating
A
80/100
Runs to the end
When it triggers w 12
50
Result and completion w 14
60
Inputs and preconditions w 11
70
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: 12. 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 80/100

    • 50When it triggers. No condition that starts the skill
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Failures and branches. 5 branches
    • 70Execution cost. Instruction body is 4766 tokens
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 125 steps
    • 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 The response is described with custom markup (8 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • -244 emoji in the instructions: noise for the model
    • +2Single-language instructions
    • +3Description length 513: enough signal without eating the budget
    • +4Structure: 37 headings
    • +3Step-by-step instructions: 125 items
    • +3Output format is stated explicitly
    • +4Has examples (8 code blocks)
    • +4Reference files are cited in the instructions (8 of 9)
    • +3All 1 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.

    External checks

    ClawHub: suspicious
    This appears to be a legitimate Alibaba Cloud WAF diagnostic skill, but it uses sensitive cloud credentials and local diagnostic files in ways that are broader and less clearly controlled than its read-only, text-only framing suggests.
    LLM: suspicious (high) · 8 Jul 2026