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gdpr-complianceGDPR 合规性

Agent Skill

用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。

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CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:gdpr-compliance(GDPR 合规性)
来源仓库:https://github.com/melodic-software/claude-code-plugins
仓库路径:skills/gdpr-compliance
安装命令:
npx skills add https://github.com/melodic-software/claude-code-plugins --skill gdpr-compliance
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/melodic-software/claude-code-plugins --skill gdpr-compliance

简介

用于辅助 GDPR 合规性检查,支持隐私政策和数据处理流程审核。

  • 适合在前端设计中集成合规性验证逻辑。gdpr-compliance 属于前端设计类 Skill,可作为该场景下的辅助能力补充。
  • 通过 GitHub 仓库安装,需确认权限范围和操作边界后再使用。
  • 建议结合原始 README 核验具体用法,避免触发不必要的联网或文件读写。
  • 使用前请检查维护状态,确保技能与当前宿主环境兼容。

SKILL.md

GDPR Compliance Planning

Comprehensive guidance for General Data Protection Regulation compliance before development begins.

When to Use This Skill

  • Planning systems that process EU residents' personal data
  • Designing consent management and preference centers
  • Implementing data subject rights (access, erasure, portability)
  • Conducting Data Protection Impact Assessments (DPIA)
  • Defining data processing agreements and controller/processor relationships

GDPR Fundamentals

The 7 Principles

PrincipleDescriptionImplementation Focus
Lawfulness, Fairness, TransparencyValid legal basis, fair processing, clear privacy noticesConsent flows, privacy policies
Purpose LimitationCollect for specified, explicit purposesPurpose tracking, use restriction
Data MinimizationAdequate, relevant, limited to purposeField-level justification
AccuracyKeep data accurate and up to dateUpdate mechanisms, verification
Storage LimitationKeep only as long as necessaryRetention policies, auto-deletion
Integrity and ConfidentialityAppropriate security measuresEncryption, access control
AccountabilityDemonstrate complianceAudit logs, documentation

Lawful Bases for Processing

1. Consent - Freely given, specific, informed, unambiguous
2. Contract - Necessary for contract performance
3. Legal Obligation - Required by law
4. Vital Interests - Protect someone's life
5. Public Task - Official authority/public interest
6. Legitimate Interest - Balanced against data subject rights

Legitimate Interest Assessment (LIA):

  1. Purpose test: Is there a legitimate interest?
  2. Necessity test: Is processing necessary for that interest?
  3. Balancing test: Do subject's interests override?

Data Subject Rights Implementation

Rights Checklist

RightDescriptionResponse TimeImplementation
AccessCopy of personal data1 monthExport endpoint
RectificationCorrect inaccurate data1 monthUpdate endpoint
Erasure ("Right to be Forgotten")Delete personal data1 monthDeletion pipeline
Restrict ProcessingLimit use of data1 monthProcessing flags
Data PortabilityMachine-readable export1 monthJSON/CSV export
ObjectStop processingWithout undue delayOpt-out mechanism
Automated Decision-MakingHuman review of decisionsVariesReview queue

.NET Implementation Patterns

// Data Subject Request Handling
public interface IDataSubjectRequestHandler
{
    Task<DataExport> HandleAccessRequest(Guid subjectId, CancellationToken ct);
    Task HandleErasureRequest(Guid subjectId, ErasureScope scope, CancellationToken ct);
    Task<PortableData> HandlePortabilityRequest(Guid subjectId, string format, CancellationToken ct);
}

public class DataSubjectRequestService : IDataSubjectRequestHandler
{
    private readonly IPersonalDataLocator _dataLocator;
    private readonly IAuditLogger _auditLogger;
    private readonly TimeProvider _timeProvider;

    public async Task<DataExport> HandleAccessRequest(Guid subjectId, CancellationToken ct)
    {
        await _auditLogger.LogRequestReceived(subjectId, "Access", _timeProvider.GetUtcNow());

        var locations = await _dataLocator.LocateAllPersonalData(subjectId, ct);
        var export = new DataExport
        {
            SubjectId = subjectId,
            GeneratedAt = _timeProvider.GetUtcNow(),
            Categories = new List<DataCategory>()
        };

        foreach (var location in locations)
        {
            var data = await location.ExtractData(ct);
            export.Categories.Add(new DataCategory
            {
                Name = location.CategoryName,
                Purpose = location.ProcessingPurpose,
                LawfulBasis = location.LawfulBasis,
                RetentionPeriod = location.RetentionPolicy,
                Data = data
            });
        }

        await _auditLogger.LogRequestCompleted(subjectId, "Access", _timeProvider.GetUtcNow());
        return export;
    }

    public async Task HandleErasureRequest(Guid subjectId, ErasureScope scope, CancellationToken ct)
    {
        // Check for legal holds or retention requirements
        var blocks = await CheckErasureBlocks(subjectId, ct);
        if (blocks.Any())
        {
            throw new ErasureBlockedException(blocks);
        }

        var locations = await _dataLocator.LocateAllPersonalData(subjectId, ct);

        foreach (var location in locations)
        {
            if (scope.IncludesCategory(location.CategoryName))
            {
                // Soft delete with scheduled hard delete
                await location.MarkForDeletion(_timeProvider.GetUtcNow().AddDays(30), ct);
            }
        }

        await _auditLogger.LogErasureInitiated(subjectId, scope, _timeProvider.GetUtcNow());
    }
}

Consent Management

// Consent tracking with granular purposes
public class ConsentRecord
{
    public Guid SubjectId { get; init; }
    public string Purpose { get; init; } = string.Empty;
    public bool IsGranted { get; init; }
    public DateTimeOffset Timestamp { get; init; }
    public string ConsentMechanism { get; init; } = string.Empty; // e.g., "WebForm", "API"
    public string ConsentVersion { get; init; } = string.Empty; // Version of consent text
    public string? WithdrawalTimestamp { get; set; }
}

public interface IConsentManager
{
    Task RecordConsent(ConsentRecord consent, CancellationToken ct);
    Task WithdrawConsent(Guid subjectId, string purpose, CancellationToken ct);
    Task<bool> HasValidConsent(Guid subjectId, string purpose, CancellationToken ct);
    Task<IReadOnlyList<ConsentRecord>> GetConsentHistory(Guid subjectId, CancellationToken ct);
}

public class GdprConsentManager : IConsentManager
{
    private readonly IConsentRepository _repository;
    private readonly IEventPublisher _events;

    public async Task<bool> HasValidConsent(Guid subjectId, string purpose, CancellationToken ct)
    {
        var latest = await _repository.GetLatestConsent(subjectId, purpose, ct);

        if (latest is null)
            return false;

        if (latest.WithdrawalTimestamp is not null)
            return false;

        // Check if consent version is still current
        var currentVersion = await _repository.GetCurrentConsentVersion(purpose, ct);
        if (latest.ConsentVersion != currentVersion)
        {
            // Consent was given under old terms - needs re-consent
            return false;
        }

        return latest.IsGranted;
    }
}

Data Protection Impact Assessment (DPIA)

When DPIA is Required

DPIA is mandatory when processing is likely to result in high risk:

  • Systematic and extensive profiling with significant effects
  • Large-scale processing of special category data
  • Systematic monitoring of public areas
  • New technologies with unknown privacy impact
  • Automated decision-making with legal/similar effects
  • Large-scale processing of children's data

DPIA Template Structure

## 1. Description of Processing
- Nature: What will you do with the data?
- Scope: How much data, how many subjects, geographic area?
- Context: Internal/external factors affecting expectations?
- Purpose: What are you trying to achieve?

## 2. Necessity and Proportionality
- Lawful basis and justification
- Purpose limitation assessment
- Data minimization measures
- Data quality approach
- Storage limitation policy

## 3. Risk Assessment

### Risks to Individuals
| Risk | Likelihood | Severity | Score | Mitigation |
|------|------------|----------|-------|------------|
| Unauthorized access | Medium | High | 6 | Encryption, MFA |
| Data breach | Low | Critical | 4 | Monitoring, IR plan |
| Inaccurate profiling | Medium | Medium | 4 | Human review |

### Residual Risk
[After mitigations applied]

## 4. Consultation
- DPO advice obtained: [Date]
- Supervisory authority consulted: [If required]
- Data subject views considered: [How]

## 5. Sign-Off
| Role | Name | Approval | Date |
|------|------|----------|------|
| Project Owner | | [ ] | |
| DPO | | [ ] | |
| CISO | | [ ] | |

Risk Scoring Matrix

         SEVERITY
         Low(1)  Medium(2)  High(3)  Critical(4)
L   High(4)    4      8         12       16
I   Med(3)     3      6          9       12
K   Low(2)     2      4          6        8
E   V.Low(1)   1      2          3        4

Thresholds:

  • 1-4: Acceptable risk
  • 5-8: Mitigations required
  • 9-12: Senior approval required
  • 13+: Consult supervisory authority

Privacy by Design Checklist

Architecture Phase

  • Data flows documented with personal data highlighted
  • Purpose for each data element defined
  • Lawful basis identified per purpose
  • Retention periods defined per category
  • Access control requirements specified
  • Encryption requirements defined
  • Pseudonymization opportunities identified

Development Phase

  • Consent collection implemented correctly
  • Data subject rights endpoints created
  • Audit logging captures processing activities
  • Data retention automation implemented
  • Encryption at rest and in transit
  • Input validation prevents excess collection
  • Error messages don't leak personal data

Testing Phase

  • Consent flows tested (grant, withdraw, re-consent)
  • All DSR endpoints functional
  • Retention automation verified
  • Access controls tested
  • Audit logs complete and accurate
  • Penetration testing for data exposure

Record of Processing Activities (ROPA)

Article 30 Requirements

Controllers must maintain records of:

Processing Activity: Customer Account Management
Controller: [Organization Name]
DPO Contact: dpo@example.com
Purposes:
  - Account authentication
  - Order fulfillment
  - Customer support
Categories of Data Subjects:
  - Customers
  - Prospective customers
Categories of Personal Data:
  - Name, email, phone
  - Address
  - Order history
  - Payment tokens (not card numbers)
Recipients:
  - Payment processor (Stripe)
  - Shipping provider (FedEx)
  - Customer support platform (Zendesk)
International Transfers:
  - Stripe Inc. (US) - SCCs
  - None to third countries without safeguards
Retention:
  - Active account: Duration of relationship
  - Closed account: 7 years (legal requirement)
Security Measures:
  - TLS 1.3 in transit
  - AES-256 at rest
  - Role-based access control
  - Regular access reviews

International Data Transfers

Transfer Mechanisms Post-Schrems II

MechanismUse CaseRequirements
Adequacy DecisionEU-approved countriesNone additional
Standard Contractual Clauses (SCCs)Most commonTIA required
Binding Corporate RulesIntra-group transfersSupervisory approval
Derogations (Art. 49)Occasional transfersLimited scope

Transfer Impact Assessment (TIA)

## Transfer Impact Assessment

### 1. Transfer Details
- Exporter: [EU entity]
- Importer: [Third country entity]
- Countries: [List]
- Data types: [Categories]
- Transfer mechanism: [SCCs/BCRs/etc.]

### 2. Third Country Assessment
- Laws requiring disclosure to authorities
- Surveillance legislation
- Rule of law / judicial independence
- Practical access by authorities

### 3. Supplementary Measures
- Technical: [Encryption, pseudonymization]
- Contractual: [Additional clauses]
- Organizational: [Policies, training]

### 4. Conclusion
- Risk level: [Acceptable/Requires mitigation/Unacceptable]
- Decision: [Proceed/Modify/Suspend]

Cross-References

  • CCPA/CPRA: See similar concepts (disclosure, deletion, opt-out)
  • AI Governance: ai-governance skill for AI-specific requirements
  • Security Frameworks: security-frameworks for technical controls
  • Data Classification: data-classification for sensitivity levels

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