privacy-compliance-engineer
A guide for implementing data privacy and security controls throughout application and database layers.
Install
mkdir -p .claude/skills/privacy-compliance-engineer && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/17417" && unzip -o skill.zip -d .claude/skills/privacy-compliance-engineer && rm skill.zipInstalls to .claude/skills/privacy-compliance-engineer
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Design and enforce privacy and data protection controls across application, API, and database layers. Use when tasks involve PII handling, retention/deletion policies, consent, data minimization, auditability, or compliance-oriented architecture changes.Key capabilities
- →Identify personal data classes, flows, and processing purpose
- →Apply minimization, masking, encryption, and least-privilege controls
- →Define retention and deletion behavior with auditable evidence
- →Add privacy-focused tests for tenant isolation and sensitive-data leakage
- →Report residual compliance risks with explicit owners and deadlines
How it works
The skill identifies personal data, applies privacy controls like minimization and encryption, defines retention policies, and adds privacy-focused tests. It reports residual compliance risks.
Inputs & outputs
When to use privacy-compliance-engineer
- →Implement data retention policy
- →Audit API for sensitive data leakage
- →Design consent-driven data flows
About this skill
Privacy Compliance Engineer
Load context first
.github/AGENTS.md.github/copilot-instructions.md.github/instructions/repository-operating-model.instructions.md
Instruction pack
.github/instructions/data-privacy-compliance.instructions.md.github/instructions/security-vulnerabilities.instructions.md.github/instructions/database.instructions.md(when data schema/queries are in scope).github/instructions/backend.instructions.md(when API/service logic is in scope)
Claude-native execution
Run as a general-purpose agent within the Super Agent pipeline.
Execution workflow
- Identify personal data classes, flows, and processing purpose.
- Apply minimization, masking, encryption, and least-privilege controls.
- Define retention and deletion behavior with auditable evidence.
- Add privacy-focused tests for tenant isolation and sensitive-data leakage.
- Report residual compliance risks with explicit owners and deadlines.
Validation examples
pwsh -File ./scripts/validation/validate-security-baseline.ps1
pwsh -File ./scripts/validation/validate-release-provenance.ps1
When not to use it
- →Tasks not involving PII handling
- →Tasks not related to retention/deletion policies
- →Tasks not focused on consent, data minimization, or auditability
Limitations
- →Requires loading context from `.github/AGENTS.md`, `.github/copilot-instructions.md`, and `.github/instructions/repository-operating-model.instructions.md`
- →Requires specific instruction packs for data privacy, security vulnerabilities, database, and backend
- →Runs as a `general-purpose` agent within the Super Agent pipeline
How it compares
This skill provides a structured workflow for designing and enforcing privacy and data protection controls across various application layers, focusing on compliance-oriented architecture changes, unlike general security engineering.
Compared to similar skills
privacy-compliance-engineer side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| privacy-compliance-engineer (this skill) | 0 | 4mo | No flags | Advanced |
| supabase-rls-policy-generator | 11 | 8mo | No flags | Advanced |
| sqlmap-database-penetration-testing | 4 | 6mo | Review | Advanced |
| data-safety-auditor | 3 | 7mo | No flags | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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