SKILLEMALL.ai

AC pipl-compliance-enhanced

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。 🎉 v1.1.9 重要更新: - 🔧 全新统一化CLI接口,简洁高效 - 📊 支持JSON/Markdown/HTML/CSV多格式报告输出 - 🧹 精简核心文件,移除冗余演示脚本 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)

ClawHub Agent Skills author: ChengQian v1.2.2 MIT-0 25 files body ≈ 3 103 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 50/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

ProcedureData and analyticsInfrastructureSecuritytype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
92
Run on models
none yet
Process rating
C
50/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    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 · 0

    ✓ No critical or high findings

    Files scanned: 24. 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 50/100

    • 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
    • 40Consistency. Frontmatter name (pipl-compliance-enhanced) differs from the folder (pipl-compliance)
    • 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
    • 100Execution cost. Instruction body is 3103 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 369: 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 5)
    • +3All 4 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.

    External checks

    ClawHub: clean
    This is a local PIPL compliance and report-generation skill with disclosed file outputs and no evidence of hidden network, credential, persistence, or destructive runtime behavior.
    LLM: benign (high) · VirusTotal: · 19 Jul 2026