SKILLEMALL.ai

AC gdpr-compliance

欧盟通用数据保护条例(GDPR)合规专用工具。覆盖合法处理基础、同意管理、 数据主体权利、DPIA、跨境传输、安全措施等核心合规领域。 🎉 v1.2.0 安全增强更新: - 🔧 全新统一化CLI接口,与PIPL、CCPA工具体验一致 - 📊 支持JSON/Markdown/HTML/CSV多格式报告 - 🚀 跨法域检查:可与PIPL、CCPA配合使用 - 🔒 纯本地运行(pandas/jinja2可选增强) - 🔒 移除 subprocess 脚本,升级依赖版本,通过安全扫描 触发关键词:GDPR、数据保护、欧盟合规、DPIA、跨境传输、 数据主体权利、DSR、数据处理协议、数据保护影响评估 适用范围:欧盟通用数据保护条例(GDPR) 运行模式:纯本地,无网络请求 ❎

ClawHub Agent Skills author: ChengQian v1.2.0 MIT-0 19 files body ≈ 2 004 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceLegalData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
C
53/100
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

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 · 0

✓ No critical or high findings

Files scanned: 19. 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 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 157 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2004 tokens
  • 100Running it twice. No mutating operations
  • low 13 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)
  • +3Output format is not stated: the model decides each time
  • -215 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 347: enough signal without eating the budget
  • +4Structure: 75 headings
  • +3Step-by-step instructions: 157 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 4 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

External checks

ClawHub: clean
This skill is a local GDPR report and template helper, with some documentation and dependency hygiene issues but no evidence of hidden data access, network transfer, or destructive behavior.
LLM: benign (medium) · VirusTotal: · 19 Jul 2026