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Cb Data Privacy Readiness Guide

作者 haidong · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install cb-data-privacy-readiness-guide
功能描述
A readiness checklist for overseas digital businesses handling customer data, covering GDPR-style principles, consent, retention, vendors, and incident respo...
使用说明 (SKILL.md)

Cross-border Data Privacy Readiness Guide

Overview

A readiness checklist for overseas digital businesses handling customer data, covering GDPR-style principles, consent, retention, vendors, and incident response.

This is a pure descriptive OpenClaw skill for overseas expansion planning. It provides frameworks, templates, checklists, decision criteria, and risk reminders. It does not execute code, call APIs, access the network, scrape websites, submit forms, make purchases, send messages, or perform any external action.

When to Use

Use this skill when the user needs structured help with cross-border data privacy readiness guide in a cross-border or international expansion context.

Typical trigger phrases include:

  • GDPR readiness
  • cross-border data privacy
  • international privacy checklist
  • overseas user data
  • privacy compliance preparation

Target Users

Founders, product managers, operations teams, marketers, and compliance coordinators preparing for overseas users.

Inputs to Collect

Ask for or infer the following context before producing the final framework:

  • Target market or list of candidate markets
  • Product, service, category, or business model
  • Current business stage and domestic traction, if any
  • Target customer segment and purchase context
  • Expansion goal, timeline, budget range, and constraints
  • Existing assets such as brand story, content, team, channels, customer data, or partners
  • Known risks, assumptions, compliance concerns, and decision deadlines

If important inputs are missing, state the assumptions clearly and provide a version that can be refined later.

Workflow

  1. Inventory the customer data the business collects, why it is collected, where it is stored, who accesses it, and which vendors process it.
  2. Map privacy obligations at a principle level: notice, consent or lawful basis, minimization, retention, access rights, deletion, security, and cross-border transfer.
  3. Identify product, marketing, analytics, support, and vendor workflows that may create privacy risk in the target market.
  4. Prioritize readiness actions such as privacy notice updates, consent review, data-retention rules, vendor review, request handling, and incident preparation.
  5. Define questions for qualified privacy counsel so the team can turn the readiness map into jurisdiction-specific compliance work.

Output Modules

Data inventory map

  • Purpose: turn the user's market context into a structured planning component.
  • Include: assumptions, recommended actions, decision criteria, and questions that require local validation.
  • Output style: concise tables, checklists, and bullet-point rationale rather than generic advice.

Consent and lawful-basis checklist

  • Purpose: turn the user's market context into a structured planning component.
  • Include: assumptions, recommended actions, decision criteria, and questions that require local validation.
  • Output style: concise tables, checklists, and bullet-point rationale rather than generic advice.

Vendor and processor review

  • Purpose: turn the user's market context into a structured planning component.
  • Include: assumptions, recommended actions, decision criteria, and questions that require local validation.
  • Output style: concise tables, checklists, and bullet-point rationale rather than generic advice.

Retention and deletion policy template

  • Purpose: turn the user's market context into a structured planning component.
  • Include: assumptions, recommended actions, decision criteria, and questions that require local validation.
  • Output style: concise tables, checklists, and bullet-point rationale rather than generic advice.

User-rights request workflow

  • Purpose: turn the user's market context into a structured planning component.
  • Include: assumptions, recommended actions, decision criteria, and questions that require local validation.
  • Output style: concise tables, checklists, and bullet-point rationale rather than generic advice.

Incident response preparation

  • Purpose: turn the user's market context into a structured planning component.
  • Include: assumptions, recommended actions, decision criteria, and questions that require local validation.
  • Output style: concise tables, checklists, and bullet-point rationale rather than generic advice.

Output Format

Return a structured response with these sections:

  1. Input Summary — what the user provided and what assumptions are being made.
  2. Strategic Diagnosis — key opportunity, constraint, and uncertainty analysis for the overseas context.
  3. Framework Output — the main tables, matrices, checklists, templates, or playbooks generated by this skill.
  4. Market Adaptation Notes — what should change by region, language, channel, customer expectation, or operating model.
  5. Risks and Validation Tasks — assumptions to test, professional review needs, and red flags.
  6. Next Actions — 5–10 practical steps the user can take manually.

Example Prompts

  • Use Cross-border Data Privacy Readiness Guide for a consumer brand entering Germany and Japan with a limited launch budget.
  • Build a practical overseas expansion framework for our SaaS product using this context: target market, audience, product category, budget, and timeline.
  • Create a cross-border data privacy readiness guide for a team that has domestic traction but no local overseas team yet.
  • Help me compare two markets and produce a checklist, decision matrix, and risk notes for GDPR readiness.

Safety and Limitations

Privacy and data-transfer rules are legal matters; use qualified privacy counsel for compliance decisions.

Additional limitations:

  • No professional legal, tax, financial, medical, employment, investment, or compliance advice.
  • No guarantee of market success, conversion improvement, legal compliance, or platform acceptance.
  • Verify local laws, platform policies, consumer expectations, and current market facts with qualified professionals and reliable sources.
  • Avoid stereotyping cultures or users; treat all cultural observations as hypotheses requiring local validation.

Acceptance Criteria

  • Creates a plain-language data inventory
  • Identifies privacy readiness gaps
  • Includes consent, retention, vendor, and access-rights checkpoints
  • Provides implementation priority levels
  • States that it is not legal advice
  • Provides structured, market-aware outputs rather than generic overseas expansion advice.
  • Includes explicit assumptions, evidence gaps, and validation steps.
  • Stays pure descriptive with no code execution, API calls, browsing, network access, or external side effects.

Publishing Notes

  • Version: 1.0.0
  • Language: English
  • Type: descriptive
  • Runtime requirements: none
  • External permissions: none
安全使用建议
This skill appears coherent and read-only: it will produce guidance and templates but not perform network calls or run code. Before using it, avoid pasting real customer PII or sensitive credentials into prompts, and treat the output as planning guidance (not legal advice)—have qualified privacy counsel validate jurisdiction-specific requirements. Also note the package lists no homepage and the source is unknown; if provenance or maintenance/author trust matters for you, verify the publisher or prefer a published guide from a known provider.
功能分析
Type: OpenClaw Skill Name: cb-data-privacy-readiness-guide Version: 1.0.0 The skill is a purely descriptive framework designed to provide checklists and readiness guides for cross-border data privacy compliance. It contains no executable code, script files, or API configurations, and explicitly states it does not perform network or system operations. All files (SKILL.md, skill.json, README.md) are consistent in describing a non-functional, advisory-only tool.
能力标签
cryptocan-make-purchases
能力评估
Purpose & Capability
The name, description, and SKILL.md consistently describe a purely descriptive privacy readiness guide. No binaries, env vars, config paths, or credentials are requested — all of which is proportionate and expected for a guidance/checklist skill.
Instruction Scope
The SKILL.md instructs the agent to collect user-provided context and produce frameworks, checklists, and templates. It explicitly states it will not execute code, call APIs, access the network, or perform external actions. There are no instructions to read system files, access unrelated environment variables, or transmit data externally.
Install Mechanism
There is no install spec and no code files; this is instruction-only. That is the lowest-risk installation model and matches the declared behavior.
Credentials
The skill requests no environment variables, credentials, or config paths. The lack of secrets or external-service tokens is appropriate for a descriptive checklist.
Persistence & Privilege
always is false, user-invocable is true, and model-invocation is allowed (the platform default). There is no request for permanent presence or modification of other skills/config; autonomous invocation is normal and not combined with other risks.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install cb-data-privacy-readiness-guide
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /cb-data-privacy-readiness-guide 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release: Cross-border Data Privacy Readiness Guide - Provides a structured checklist for data privacy readiness in overseas digital expansion, covering GDPR-style principles, consent, retention, vendors, and incident response. - Offers modular outputs: data inventory map, consent checklist, vendor review, retention/deletion template, user rights workflow, and incident response preparation. - Guides users to collect key context (target markets, product details, business stage, customer segments, etc.) and clarifies assumptions when information is missing. - Delivers clear, structured outputs including summaries, diagnostics, frameworks, adaptation notes, risk reminders, and next actions. - Purely descriptive: does not offer legal advice or execute code; emphasizes the need for professional compliance review.
元数据
Slug cb-data-privacy-readiness-guide
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Cb Data Privacy Readiness Guide 是什么?

A readiness checklist for overseas digital businesses handling customer data, covering GDPR-style principles, consent, retention, vendors, and incident respo... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 59 次。

如何安装 Cb Data Privacy Readiness Guide?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install cb-data-privacy-readiness-guide」即可一键安装,无需额外配置。

Cb Data Privacy Readiness Guide 是免费的吗?

是的,Cb Data Privacy Readiness Guide 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Cb Data Privacy Readiness Guide 支持哪些平台?

Cb Data Privacy Readiness Guide 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Cb Data Privacy Readiness Guide?

由 haidong(@harrylabsj)开发并维护,当前版本 v1.0.0。

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