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BD ct-security-patrol

智能体安全管家：专为openclaw、teleclaw等智能体产品研发的检查和防护工具，本工具默认提供本地离线扫描，也可选择联网威胁情报关联分析。 功能范围：读取系统敏感信息（MAC 地址、主机名、系统日志、完整 Skill 清单）执行本地安全检测；在本机持久化保存扫描报告与安全基线；可选通过 --push 模式将摘要数据上传至 auth.ctct.cn 获取威胁情报评分（需用户显式同意）；可选通过 openclaw cron 设置定时任务（绑定 openclaw 基础设施，可跳过）。 运行依赖：Node.js v18+。本技能由 Changeway 团队（auth.ctct.cn 运营方）开发。 使用场景：用户说"安全巡检"、"安全检查"、"安全审计"、"巡检"、"security audit"、"检查安全"、"系统安全"等。 触发条件：任何与 OpenClaw 安全检测、审计、巡检相关的请求。

ClawHub Agent Skills author: SMBBWS2 v1.0.0 MIT-0 4 files body ≈ 1 801 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerInfrastructuretype 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
87/100
safety, quality, tests
Safety 60%
95
Quality 40%
74
Run on models
none yet
Process rating
D
43/100
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 · 5

✓ No critical or high findings

Medium and low: 5
  • low Dangerous commands cmd-cron-mention references/cron-setup.md:127
    Mentions editing / listing crontab (documentation of a security skill)
    crontab -e  # 删除相关行
    security skill

A further 4 matches are quotations in this security skill's documentation and are not counted as findings.

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "runtime"
  • note frontmatter-key unknown frontmatter key "credentials"
  • note frontmatter-key unknown frontmatter key "privacy"
  • note frontmatter-key unknown frontmatter key "network_endpoints"
  • note frontmatter-key unknown frontmatter key "dependencies"
  • note frontmatter-key unknown frontmatter key "security_notes"

Process rating: all ten parameters 43/100

  • 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
  • 30Running it twice. 10 mutating operations with no state check
  • 60Tools and files. Uses tools (node) that frontmatter does not declare
  • 100Steps. 45 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1801 tokens
  • low The response is described with custom markup (3 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)
  • +3Output format is not stated: the model decides each time
  • -212 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 404: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 45 items
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: suspicious
This is a purpose-aligned security scanner, but it needs Review because its default local mode creates a persistent device identifier despite documentation saying that only happens with upload mode.
LLM: suspicious (high) · VirusTotal: · 29 May 2026