AC pipl-compliance
中国个人信息保护法（PIPL）合规检查、风险评估和文档生成工具。 为企业提供全面的PIPL合规解决方案。 Use when: 需要进行PIPL合规自查、个人信息处理风险评估、 合规文档生成、企业合规管理、数据处理影响评估、跨境传输合规检查。 🎉 v1.2.2 重要更新： - 🔒 安全扫描全部通过，依赖版本锁定（修复 CVE 漏洞） - 📊 支持 JSON/Markdown/HTML/CSV 多格式报告输出 - 📋 新增"small_processor_audit"场景：基于《小型个人信息处理者个人信息保护简化措施规定》（国家互联网信息办公室、公安部令第25号，2026-09-01施行）附件1的24项审计框架 - 🔗 法规参考文档：references/2026-simplified-measures.md - 🧹 精简超出 PIPL 范围的脚本，MCP 最小权限声明 触发关键词：PIPL、个人信息保护法、合规检查、风险评估、 隐私合规、数据保护、跨境传输、影响评估 适用范围：中华人民共和国个人信息保护法（PIPL） 运行模式：纯本地，无网络请求 ❎ 外部依赖：Python标准库 + pandas（可选，增强数据分析） + jinja2（可选，增强文档模板渲染）
中国个人信息保护法（PIPL）合规检查、风险评估和文档生成工具。 为企业提供全面的PIPL合规解决方案。 Use when: 需要进行PIPL合规自查、个人信息处理风险评估、 合规文档生成、企业合规管理、数据处理影响评估、跨境传输合规检查。 🎉 v1.2.2 重要更新： - 🔒…
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: 28. 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, web, python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 100Steps. 178 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3092 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
- low 17 top-level sections: this looks like several domains in one skill
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)
- -252 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 548: enough signal without eating the budget
- +4Structure: 86 headings
- +3Step-by-step instructions: 178 items
- +3Output format is stated explicitly
- +4Has examples (14 code blocks)
- +4Reference files are cited in the instructions (1 of 6)
- +3All 4 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.