AC privacy-check
隐私敏感信息扫描器 (Privacy Check) v1.0.1。 检测15+种敏感个人信息：身份证号、手机号、邮箱、银行卡、信用卡、 SSN、护照、驾驶证、微信号、支付宝号、API密钥等。 支持 JSON/CSV/HTML 报告输出、白名单忽略、文件类型过滤。 Use when: 需要在数据文件中发现敏感信息、 数据发布前做隐私审查、合规检查准备、数据脱敏预处理。 🎉 v1.0.1 安全增强更新： - 6 种新增PII模式（信用卡、SSN、港澳台护照、驾驶证、微信号、支付宝） - CSV / HTML 报告格式 - 白名单忽略模式 - 文件扩展名过滤 - 🔒 上下文行自动脱敏，避免敏感数据聚合泄露 - 🔒 上下文默认关闭（--context 开启），减少敏感数据聚合风险 - 🔒 报告头部增加安全警告 - ASCII 条形图摘要 v1.0.0 核心功能： - 🔍 10+ 种敏感信息模式检测 - 🎭 自动脱敏显示 - 📊 JSON 报告输出 - 🚀 纯本地运行，无外部依赖 触发关键词：隐私检查、PII扫描、敏感信息检测、 数据合规、脱敏、隐私审计、个人信息保护 适用范围：任意文本文件（TXT/CSV/JSON/日志等） 运行模式：纯本地，无网络请求 ❎ 外部依赖：Python标准库（无需额外安装）
隐私敏感信息扫描器 (Privacy Check) v1.0.1。 检测15+种敏感个人信息：身份证号、手机号、邮箱、银行卡、信用卡、 SSN、护照、驾驶证、微信号、支付宝号、API密钥等。 支持 JSON/CSV/HTML 报告输出、白名单忽略、文件类型过滤。 Use when: 需要在数据文件中发现敏感信息、…
As a process C 55/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches
How to improve
- 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 · 0
✓ No critical or high findings
Files scanned: 7. 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 55/100
- 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
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 100Steps. 5 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 397 tokens
- 100Running it twice. No mutating operations
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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)
- +1No license
- +2Single-language instructions
- +3Description length 568: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 5 items
- +3Output format is stated explicitly
- +4Has examples (4 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.