Privacy By Design
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Written by AutoGineer from the skill’s own files, not by the author
The Privacy by Design (PbD) skill provides a comprehensive knowledge base and assessment protocol for evaluating software systems against the 7 Foundation Principles established by Dr. Ann Cavoukian. It enables users to conduct proactive privacy reviews, identify deficiencies, and map findings to regulatory requirements including GDPR, CCPA/CPRA, and Australian Privacy Principles. The skill includes structured checklists, implementation patterns, and a finding schema to ensure consistent, evidence-based privacy assessments across the development lifecycle.
What it does
- Assesses system designs against the 7 Foundation Principles of Privacy by Design.
- Provides a structured protocol for conducting privacy impact assessments.
- Maps privacy findings to GDPR, CCPA/CPRA, and Australian Privacy Principles.
- Evaluates data retention, disposal, and lifecycle management practices.
- Identifies privacy-related anti-patterns in architecture and configuration.
- Generates actionable remediation items for identified privacy deficiencies.
When to use it
- During the design phase of a new system or feature involving personal data.
- When performing a proactive privacy audit to identify potential compliance gaps.
- To verify that privacy controls are embedded into the architecture rather than added post-deployment.
- When establishing data retention and disposal schedules for sensitive information.
- To generate structured privacy assessment reports for stakeholders.
Advantages
- Promotes a proactive, preventative approach to privacy rather than reactive compliance.
- Standardizes privacy assessments using a clear, evidence-based schema.
- Facilitates cross-jurisdictional compliance mapping.
- Integrates privacy considerations directly into the software development lifecycle.
- Provides clear, actionable remediation guidance for identified risks.
Usage examples
- “Assess our new user registration flow against the 7 Privacy by Design principles.”
- The agent will walk through each of the 7 principles, checking for proactive design, default privacy settings, and end-to-end security, ultimately providing a compliance verdict and specific remediation steps.
- “Check our data retention policy for compliance with PbD-05.”
- The agent will evaluate the current retention and disposal lifecycle against Principle 05, identifying gaps in data minimization or legal hold procedures and suggesting improvements.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/microsoft/privacy-by-design/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip privacy-by-design.zip -d .agents/skills
Documentation by Microsoft
Privacy by Design
This SKILL.md is the entrypoint for the Privacy by Design skill.
The skill provides structured assessment references for the 7 Foundation Principles of Privacy by Design (Cavoukian, 2009). Consumers that explicitly load it can assess privacy practices across the software lifecycle. It complements privacy-standards with principle-level criteria, retention and disposal checks, regulatory mappings, a finding schema and implementation patterns. Current agent wiring is described under Integration below.
[!NOTE] This skill is a planning aid, not legal advice. Its standards summaries support privacy reasoning and review preparation; they do not substitute for qualified legal counsel or a formal regulatory interpretation.
Goal
Produce an evidence-based assessment against the 7 PbD Foundation Principles, with per-principle verdicts, explicit evidence gaps, deficiency severity, and remediation for established deficiencies. Assessment labels describe this planning rubric, not legal certification.
Success criteria
All 7 principles have a verdict, evidence completeness, and severity (
N/Awhen no deficiency is established).Each FAIL or PARTIAL finding includes a specific, actionable remediation.
Findings use the structured schema defined in
finding-schema.md.Cross-jurisdictional obligations are identified for the applicable regulatory scope.
Retention and disposal are assessed for any system that stores personal data.
An overall assessment verdict (COMPLIANT / PARTIALLY_COMPLIANT / NON_COMPLIANT / INCOMPLETE) is determined without treating missing evidence as a failed control.
Finding, principle, checklist and severity counts reconcile under the finding schema.
When to use this skill
Use when you need to:
Assess a system, feature, or data flow against the 7 PbD Foundation Principles
Verify that privacy is embedded proactively (not bolted on after incidents)
Check data retention schedules, disposal methods, and legal hold procedures
Map privacy requirements across GDPR Art. 25, CCPA/CPRA, and Australian Privacy Principles
Generate per-principle PASS/PARTIAL/FAIL/INSUFFICIENT_EVIDENCE results with evidence-backed severity
Identify code-level and configuration-level privacy patterns or anti-patterns
Produce backlog items from privacy assessment findings
Do not use for:
General privacy standards mapping without principle assessment (use
privacy-standards)Security threat modeling (use
security-planningor OWASP skills)RAI assessment (use
rai-planner)Legal advice or regulatory compliance certification
Stop rules
Stop the assessment if the system boundary cannot be established.
Stop and escalate if processing occurs in a jurisdiction not covered by this skill's mappings.
Do not fabricate evidence; record
INSUFFICIENT_EVIDENCEand the evidence needed. Continue supported checks without inventing deficiency remediation for unknowns.Do not provide legal opinions; frame all findings as planning guidance requiring qualified review.
Do not duplicate security findings that the
security-planningskill already covers; cross-reference them.
Normative references (PbD 7 Foundation Principles)
Operational references
Assessment Protocol — step-by-step protocol for conducting a PbD assessment
Finding Schema — structured output format for findings and backlog handoff
Implementation Patterns — pragmatic code-level and architecture-level verification patterns
Supplementary references
Data Retention and Disposal — Principle 05 deep-dive: retention schedules, disposal methods, legal holds
Cross-Jurisdictional Mapping — regulatory equivalence matrix across GDPR, CCPA/CPRA, and APP
Industry Privacy Profiles — sector-specific principle priorities, checks, and
.pbd-config.ymlcustomization
Skill layout
SKILL.md— this file (skill entrypoint).references/— the PbD normative documents, operational guides, and supplementary material.00-principle-index.md— index of all principle identifiers, categories, source mappings, and cross-references.01through07— one document per PbD Foundation Principle with checklist, controls, anti-patterns, and regulatory mappings.assessment-protocol.md— phased assessment protocol for agents conducting PbD reviews.finding-schema.md— YAML-based finding and summary schema for structured output.implementation-patterns.md— code-level and configuration-level patterns agents can verify.data-retention-and-disposal.md— Principle 05 deep-dive: retention schedules, disposal methods, legal holds.cross-jurisdictional-mapping.md— regulatory equivalence matrix across GDPR, CCPA/CPRA, and APP.industry-privacy-profiles.md— telco, healthcare, financial sector profiles with.pbd-config.ymlcustomization schema.
Citation-field vocabulary
Use these fields when capturing a finding so the reviewer can assert a stable source-control reference:
pbd_principle: Principle number (1–7) with short name, e.g.,PbD-01 Proactive Not Reactivegdpr_article: GDPR article reference, e.g.,Art. 25app_principle: Australian Privacy Principle number, e.g.,APP 1ccpa_section: CCPA/CPRA section reference
Finding severity conventions
| Severity | Meaning |
|---|---|
| CRITICAL | Established deficiency with severe direct risk, or FAIL under an effective CRITICAL industry priority |
| HIGH | Principle is violated with direct risk to data subjects |
| MEDIUM | Principle is partially met; gaps exist that could lead to non-compliance |
| LOW | Minor gap; principle intent is largely met but documentation or controls could improve |
| N/A | No deficiency established, including PASS and unknown-only results |
Data sensitivity informs the impact of a proven deficiency; it does not create one. Preserve CRITICAL in records and summaries. CRITICAL and HIGH map to P1, with CRITICAL ordered first; MEDIUM maps to P2 and LOW to P3. PASS and unknown-only results do not create remediation backlog items.
Finding verdict conventions
| Verdict | Meaning |
|---|---|
| PASS | All applicable checks are MET, with no unresolved evidence or anti-patterns |
| PARTIAL | A deficiency is established but the FAIL threshold is not met |
| FAIL | More than half of applicable checks are NOT MET, or an uncompensated critical anti-pattern is established |
| INSUFFICIENT_EVIDENCE | No deficiency established, but unknown evidence or zero applicable checks prevents PASS |
Apply the ordered rules in the assessment protocol. Record evidence completeness independently so a proven deficiency is not hidden by unknown checks. Suppressions require a documented applicability reason and do not count as MET.
Overall assessment verdicts
| Verdict | Condition |
|---|---|
| NON_COMPLIANT | One or more principles are FAIL; retain any evidence gaps separately |
| INCOMPLETE | No FAIL, but any principle or applicable retention/jurisdiction check has incomplete evidence |
| PARTIALLY_COMPLIANT | Complete evidence, no FAIL, and at least one PARTIAL |
| COMPLIANT | Complete evidence and all 7 principles PASS |
Evaluate these rows in order. Never use null for a verdict or interpret an unknown jurisdictional baseline as met or failed.
Integration with Privacy Planner and Reviewer
This skill complements privacy-standards (which provides the NIST PF, GDPR, CCPA, OWASP backbone). A consumer performing PbD assessment should explicitly load both:
privacy-standards— standards mapping, data-flow reasoning, DPIA thresholdsprivacy-by-design— principle-level assessment, retention/disposal checks, cross-jurisdictional equivalence, implementation pattern verification
The current Privacy Planner and Privacy Reviewer do not explicitly load privacy-by-design. This skill supplies assessment knowledge, not automatic integration; dedicated agent wiring is outside this skill change. It remains background-only (user-invocable: false).
Interaction with other skills
| Skill | Relationship |
|---|---|
privacy-standards | Provides data inventory, DPIA thresholds, and standards backbone; PbD builds on top |
security-planning | Security controls overlap with PbD-05; reference rather than duplicate |
rai-planner | RAI data-use concerns feed into PbD-04 (full functionality) and PbD-07 (user respect) |
secure-by-design | SBD-11 (Secure Deprecation) aligns with PbD-05 lifecycle; cross-reference for decommissioning |
Attribution and licensing posture
SKILL.md and references/ contain original assessment guidance and paraphrased summaries under CC BY 4.0. The cited publications remain authoritative and retain their own rights; this license does not relicense upstream text. Principle names and legal identifiers are preserved for traceability. No upstream document is reproduced or bundled.
Cavoukian PbD Foundation Principles
Author: Dr. Ann Cavoukian, Information and Privacy Commissioner of Ontario
Source: https://www.ipc.on.ca/sites/default/files/legacy/2018/01/pbd.pdf
Modifications: Principles restructured into agent-consumable assessment checklists with cross-references to GDPR, CCPA, and APP; original principle text paraphrased with attribution
Note: The 7 Foundation Principles are widely referenced in academic and regulatory literature; content here is paraphrased for planning use
GDPR Art. 25 (Data Protection by Design and by Default)
Modifications: Mapped to PbD principles as regulatory equivalence; paraphrased with attribution
Australian Privacy Principles (APP)
Source: https://www.oaic.gov.au/privacy/australian-privacy-principles
Copyright: © Commonwealth of Australia
Modifications: Mapped to PbD principles as cross-jurisdictional equivalence; paraphrased with attribution
CCPA/CPRA
Source: https://oag.ca.gov/privacy/ccpa
Modifications: Mapped to PbD principles as cross-jurisdictional equivalence; paraphrased with attribution
Files
- ATTRIBUTION.mdAdded by AutoGineer977 B
- LICENSEAdded by AutoGineer16.6 KiB
- SKILL.md12.9 KiB
- references/00-principle-index.md4.0 KiB
- references/01-proactive-not-reactive.md4.4 KiB
- references/02-privacy-as-the-default.md4.5 KiB
- references/03-privacy-embedded-into-design.md4.7 KiB
- references/04-full-functionality.md4.4 KiB
- references/05-end-to-end-security.md5.8 KiB
- references/06-visibility-and-transparency.md5.6 KiB
- references/07-respect-for-user-privacy.md5.5 KiB
- references/assessment-protocol.md9.7 KiB
- references/cross-jurisdictional-mapping.md13.3 KiB
- references/data-retention-and-disposal.md7.1 KiB
- references/finding-schema.md10.8 KiB
- references/implementation-patterns.md10.1 KiB
- references/industry-privacy-profiles.md11.3 KiB
references/assessment-protocol.md
title: Assessment Protocol description: Step-by-step protocol for agents assessing a system against PbD 7 Foundation Principles
Assessment Protocol
Consumers that explicitly load privacy-by-design use this protocol to assess a system, feature, or data flow against the 7 Foundation Principles. It defines intended assessment behavior, not an existing load step in the Privacy Reviewer or Privacy Planner.
Assessment entry conditions
Begin a PbD assessment when any of these conditions hold:
A new feature or system processes personal data and has not been assessed against PbD principles.
A privacy review is requested during design, architecture, or pre-release review.
A DPIA (from the
privacy-standardsskill) identifies high-risk processing that warrants principle-level analysis.A data retention audit is triggered by regulatory change or incident response.
Assessment phases
Phase 1: Scope and context
Identify the system, feature, or data flow under assessment.
Determine the personal data categories involved (using the data inventory from
privacy-standards).Identify applicable jurisdictions (use
cross-jurisdictional-mapping.mdtriggers).Establish the assessment boundary: which components, services, and data stores are in scope.
Document the processing purposes and lawful bases for each data category.
Load the applicable industry profile, including justified overrides, custom checks and suppressions from
.pbd-config.yml. Record the effective checklist before scoring.
Phase 2: Principle-by-principle assessment
For each principle (PbD-01 through PbD-07):
Read the principle reference file.
Evaluate each item in the principle checklist against the system evidence.
For each checklist item, record one of:
MET — evidence confirms the indicator is satisfied.
NOT MET — evidence confirms the indicator is violated or absent.
INSUFFICIENT EVIDENCE — cannot determine from available information.
Check for anti-patterns listed in the principle reference.
Assign PASS, PARTIAL, FAIL, or INSUFFICIENT_EVIDENCE using the ordered verdict rules below. Record evidence completeness independently.
Assign CRITICAL, HIGH, MEDIUM, or LOW only for an established deficiency; otherwise use N/A.
Record the finding with citation fields from the principle reference.
Phase 3: Retention and disposal assessment
When the system stores personal data:
Verify retention schedules exist for each data category (use
data-retention-and-disposal.md).Check that retention periods are purpose-linked and justified.
Verify disposal methods are appropriate for the data sensitivity.
Check backup and replica inclusion in retention policies.
Verify legal hold procedures exist if the system could be subject to litigation holds.
Record retention-specific findings under PbD-05.
Phase 4: Cross-jurisdictional check
When multiple jurisdictions apply:
Use the jurisdictional scope triggers in
cross-jurisdictional-mapping.md.Identify which regulations apply to each data flow.
Assess each applicable obligation against evidence; a shared baseline does not replace jurisdiction-specific requirements. Record the common baseline as MET, NOT_MET, INSUFFICIENT_EVIDENCE, or NOT_APPLICABLE rather than inferring a boolean from missing evidence.
Flag any jurisdiction-specific obligations not met by the common baseline.
Record cross-jurisdictional findings with the applicable regulation and article.
Phase 5: Synthesis and handoff
Aggregate findings into a summary with counts by verdict and severity.
Order actionable findings by severity: CRITICAL, HIGH, MEDIUM, LOW; within a tier, FAIL before PARTIAL. CRITICAL and HIGH both map to P1 without downgrading CRITICAL or inventing P0.
For each FAIL or PARTIAL finding, provide a specific, actionable remediation recommendation.
Apply the finding schema's overall verdict rules, preserving unknowns and evidence requests separately from remediation. COMPLIANT describes this rubric only, not legal sign-off.
Hand off findings in the finding schema format (see
finding-schema.md).
Verdict rules
Evaluate these rules in order for the effective applicable checklist:
FAIL when more than half of applicable items are NOT MET, or a critical anti-pattern is established without effective compensating controls. Unknown items stay in the denominator, never in the NOT MET count.
PARTIAL when at least one deficiency or compensated anti-pattern is established and the FAIL rule does not apply. This includes ties and mixed known deficiencies with missing evidence.
INSUFFICIENT_EVIDENCE when no deficiency is established but any item is unknown, or no applicable items remain. Identify the evidence or scope needed; never emit a vacuous PASS.
PASS only when at least one applicable item remains, all are MET, and no unresolved anti-pattern or contradiction remains.
Use the same rules for a sub-check's scoped items. A confirmed anti-pattern is a deficiency even when checklist counts alone appear favorable. Record evidence_status: INCOMPLETE if any applicable item, anti-pattern investigation, retention obligation or jurisdictional check remains unknown; otherwise use COMPLETE. Missing artifacts are not proof that a control is absent.
Fold retention, industry/custom checks and jurisdiction-specific deficiencies into the affected principle's assessment. Do not let a sub-finding disappear behind a principle PASS. Cross-jurisdictional findings identify the affected principles; include the corresponding obligation in each applicable checklist once, not duplicate evidence counts within a principle.
Severity rules
| Severity | Condition |
|---|---|
| CRITICAL | Established deficiency with severe direct impact, or FAIL under an effective CRITICAL profile/override priority |
| HIGH | Established deficiency with direct risk to data subjects or applicable obligations |
| MEDIUM | Established control gap with limited or indirect impact |
| LOW | Established documentation or process deficiency with no demonstrated direct impact |
| N/A | No established deficiency, including PASS and unknown-only results |
Determine the deficiency first, then its impact. Sensitive data alone cannot elevate PASS or unknown-only results. Apply a failed custom check's configured severity and the profile escalation rule without lowering an otherwise justified severity. A principle's severity is the highest severity of its established deficiencies; use N/A when none exist.
Evidence expectations
Record evidence source, scope and observation date where available. Distinguish intended policy from deployed behavior. When sources conflict, compare their scope, version and timing; retain both and explain which conclusion they support. If the conflict cannot be reconciled, mark the affected check unknown rather than assuming PASS. A verified operational contradiction is NOT MET, not merely missing evidence.
For PbD-06, verify that notices accurately describe current practice. A promise to destroy eSIM profiles within 30 days contradicted by recoverability at day 120 establishes a transparency deficiency and a related PbD-05 retention issue unless an applicable, disclosed exception explains it. Preserve MET credit for independently verified notice accessibility, contact routes and other unaffected controls. Cross-reference the two issues rather than duplicating remediation for the same cause.
Acceptable evidence for MET determinations:
Architecture documents or ADRs showing privacy-by-design decisions
Code showing privacy controls (encryption, access control, data minimization, consent mechanisms)
Configuration files showing privacy-protective defaults
Data flow diagrams showing personal data boundaries
Retention schedule documents
Privacy impact assessments or DPIA records
Test cases covering privacy behaviors
Monitoring or alerting configurations for privacy-relevant events
Interaction with other skills
| Skill | Interaction |
|---|---|
privacy-standards | Provides data inventory, DPIA thresholds, and standards backbone; PbD assessment builds on top |
security-planning | Security controls overlap with PbD-05; reference security findings rather than duplicating |
rai-planner | RAI assessment may identify data use concerns that feed into PbD-04 and PbD-07 |
Stop rules
Stop the assessment if scope cannot be established (no identifiable system or data flow).
Stop and escalate if the system processes data in a jurisdiction not covered by this skill's mappings.
Do not fabricate evidence; record INSUFFICIENT EVIDENCE and note what is needed.
Do not provide legal opinions; frame all findings as planning guidance requiring qualified review.
Protocol synthesized from the assessment patterns used by the Security Reviewer and RAI Planner within hve-core, adapted for privacy principle assessment.
Source principles: IPC Ontario, Privacy by Design. Assessment rules and output conventions are repository-original planning guidance.
Requirements and compatibility
Written for: GitHub Copilot, Claude Code
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Claude Code frontmatter
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Attribution and licence
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- Microsoft
- Publisher
- Microsoft (Official)
- Source
- microsoft/hve-core · .github/skills/project-planning/privacy-by-design · commit f425e94
- Licence
- Creative Commons Attribution 4.0 International (redistribution allowed)
- LICENSE (written by AutoGineer)
- ATTRIBUTION.md (written by AutoGineer)
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