BD skill-audit
AI Agent技能安全扫描工具。自动扫描已安装的OpenClaw技能，发现安全隐患。支持定时扫描（每24小时），自动发送报告到配置的所有Channel（Telegram/飞书等）。检测硬编码凭证、Shell注入、网络泄露等安全威胁。
As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
AnalyzerTelegramInfrastructureAI and agentstype and topics are labelled automatically from the skill text
How to improve
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
low Exfiltration
net-credential-usereferences/security-checks.md:17Credential used in a network call (verify the destination is the intended service) (documentation table row; documentation of a security skill)| Environment exfiltration | `os.environ[key]` → `requests.post()` | Sends secrets to external servers |
tablesecurity skill
Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription 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 (skill-audit) differs from the folder (skill-audit-pro)
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 100Steps. 18 steps
- 100Execution cost. Instruction body is 255 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 117: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -214 emoji in the instructions: noise for the model
- -41 reference files, but SKILL.md never points to them: the model will not open them
- -32 of 2 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +4Structure: 10 headings
- +3Step-by-step instructions: 18 items
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.
External checks
ClawHub: suspicious
This appears to be a real skill-security scanner, but it needs review because it runs recurring scans and prepares reports for all discovered messaging channels without clear recipient or disable controls.
LLM: suspicious (high) · VirusTotal: · 29 May 2026