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BD MiaoQIDS

量子入侵检测系统技能喵～ 基于经典-量子混合神经网络的入侵检测系统，可以分析网络流量数据（PCAP 文件），检测多种攻击类型，并为每种攻击提供置信度喵～ 提供安全防护建议喵。

ClawHub Agent Skills author: tsherryyann v0.1.1 MIT-0 10 files body ≈ 1 029 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceInfrastructuretype 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
B
83/100
safety, quality, tests
Safety 60%
98
Quality 40%
60
Run on models
none yet
Process rating
D
41/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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
  • low Secrets in code secret-high-entropy-token IPv6_calculate.py:28
    High-entropy token-like string (may be an id, hash or a credential)
    network_int=ipv6_to_int(ipv6_list[0])&(0xFF…FFF<<(128-…len))
  • low Secrets in code secret-high-entropy-token IPv6_calculate.py:44
    High-entropy token-like string (may be an id, hash or a credential)
    network_ip=min_ip&(0xFF…FFF<<(128-…its))

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

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 41/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (MiaoQIDS) differs from the folder (miao-qids)
  • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
  • 100Steps. 20 steps
  • 100Execution cost. Instruction body is 1029 tokens
  • 100Running it twice. No mutating operations

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)
  • +3Description length 87: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • -214 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 20 items
  • +4Has examples (6 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.

External checks

ClawHub: suspicious
This PCAP intrusion-detection skill mostly matches its stated purpose, but it needs Review because it loads unverified executable model files and sends extracted IP addresses to an outside service without clear consent.
LLM: suspicious (high) · VirusTotal: · 29 May 2026