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OpenClaw 安全审计与防护系统。当需要记录敏感操作、生成审计报告、查询历史操作记录、分析安全风险、执行两阶段确认拦截、扫描外部内容安全、检测文件完整性时激活。触发场景包括：用户要求查看操作记录、生成每日/每周审计报告、查询特定操作历史、分析高危操作、执行清理旧日志、高危操作需二次确认、检测操作速率异常、扫描外部URL/文本内容、验证skill文件完整性。

ClawHub Agent Skills author: yangdongmingisok v1.0.0 MIT-0 11 files body ≈ 1 242 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 55/100 · Has gaps — 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
C
67/100
safety, quality, tests
Safety 60%
63
Quality 40%
73
Run on models
none yet
Process rating
C
55/100
Has gaps
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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Secrets in code 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 files contain someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.

For the author

The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.

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 · 13

✓ No critical or high findings

Medium and low: 13
  • medium Secrets in code secret-labelled-token scripts/audit_feishu.py:20
    Labelled token / key literal (vendor format unknown — verify it is not a live credential)
    APP_SECRET = "GjLe…XeF"
  • medium Secrets in code secret-labelled-token scripts/chain_analyzer.py:14
    Labelled token / key literal (vendor format unknown — verify it is not a live credential)
    APP_SECRET = "GjLe…XeF"
  • medium Secrets in code secret-labelled-token scripts/confirm.py:20
    Labelled token / key literal (vendor format unknown — verify it is not a live credential)
    APP_SECRET = "GjLe…XeF"
  • medium Secrets in code secret-labelled-token scripts/rate_monitor.py:14
    Labelled token / key literal (vendor format unknown — verify it is not a live credential)
    APP_SECRET = "GjLe…XeF"
  • medium Secrets in code secret-labelled-token scripts/skill_integrity.py:16
    Labelled token / key literal (vendor format unknown — verify it is not a live credential)
    APP_SECRET = "GjLe…XeF"
  • medium Secrets in code secret-labelled-token scripts/url_guard.py:15
    Labelled token / key literal (vendor format unknown — verify it is not a live credential)
    APP_SECRET = "GjLe…XeF"
  • low Secrets in code secret-high-entropy-token scripts/audit_feishu.py:20
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    APP_SECRET = "GjLe…XeF"
    quoted
  • low Secrets in code secret-high-entropy-token scripts/chain_analyzer.py:14
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    APP_SECRET = "GjLe…XeF"
    quoted
  • low Secrets in code secret-high-entropy-token scripts/confirm.py:20
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    APP_SECRET = "GjLe…XeF"
    quoted
  • low Secrets in code secret-high-entropy-token scripts/rate_monitor.py:14
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    APP_SECRET = "GjLe…XeF"
    quoted
  • low Secrets in code secret-high-entropy-token scripts/skill_integrity.py:16
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    APP_SECRET = "GjLe…XeF"
    quoted
  • low Secrets in code secret-high-entropy-token scripts/url_guard.py:15
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    APP_SECRET = "GjLe…XeF"
    quoted

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

Files scanned: 11. 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")

Process rating: all ten parameters 55/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 100Tools and files. No external tools needed
  • 100Steps. 17 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1242 tokens
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress

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
  • -227 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 181: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 17 items
  • +4Has examples (15 code blocks)
  • +3All 9 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: suspicious
This security-audit skill is broadly coherent, but it sends sensitive audit and approval data to fixed Feishu accounts using embedded credentials that installers cannot control.
LLM: suspicious (high) · VirusTotal: malicious · 28 May 2026