Project 16: Privacy, Terms, and Data Disclosure Pack

Convert implementation reality into public legal artifacts that satisfy submission requirements and user trust expectations.

Quick Reference

Attribute Value
Difficulty Intermediate
Time Estimate 1 week
Main Programming Language N/A (documentation engineering)
Alternative Programming Languages TypeScript for validators
Coolness Level Level 3
Business Potential Mandatory for launch
Prerequisites Data-flow understanding, release checklist basics
Key Topics Privacy policy, terms of use, data disclosures, legal drift prevention

1. Learning Objectives

  1. Build a data inventory tied to tool behavior.
  2. Publish privacy policy and terms on verified domain.
  3. Map legal claims to technical evidence.
  4. Prevent disclosure drift across releases.

2. All Theory Needed (Per-Concept Breakdown)

Fundamentals Legal pages are part of the product contract. If disclosures and behavior diverge, approval and trust both fail.

Deep Dive into the concept Start from data inventory, not legal templates. For each workflow, list collected data, purpose, storage location, retention period, and deletion path. Then draft policy text that matches these facts exactly.

Terms and privacy pages should include version/date, contact channel, and clear boundaries. Host on verified domain and validate URL health in release checks. Add a release rule: any data-flow change requires policy review.

Treat legal claims as testable. If you claim “retained for 30 days,” show automated evidence. If you claim deletion on request, document workflow and response timeline.

Minimal concrete example

claim: "Audit logs retained 30 days"
evidence: retention-job-report-2026-02-10.json
status: verified

3. Project Specification

3.1 What You Will Build

A legal readiness pack: privacy policy, terms of use, data handling matrix, and CI validation checks.

3.2 Functional Requirements

  1. Publish privacy and terms pages over HTTPS.
  2. Build data inventory and disclosure mapping.
  3. Add release checks for legal link health and versioning.
  4. Document retention/deletion evidence.

3.3 Real World Outcome

$ npm run legal:verify
[ok] privacy url reachable
[ok] terms url reachable
[ok] policy version/date present
[ok] data categories documented
[ok] retention/deletion evidence linked
legal_readiness=pass

4. Solution Architecture

Data Inventory -> Policy Drafting -> Verified Domain Hosting -> CI Validation -> Release Approval

5. Implementation Guide

5.1 The Core Question You’re Answering

“Can we prove our public privacy/terms commitments match actual implementation behavior?”

5.2 Concepts You Must Understand First

  1. Data inventory and classification.
  2. Retention/deletion control design.
  3. Release-linked legal versioning.

5.3 Questions to Guide Your Design

  1. Which data items are essential vs unnecessary?
  2. How is each policy claim verified technically?
  3. How are policy updates triggered and approved?

5.4 Thinking Exercise

Draft a claim-to-evidence table for one workflow and identify any claims without verifiable controls.

5.5 The Interview Questions They’ll Ask

  1. How do you avoid legal disclosure drift?
  2. Which claims require hard technical evidence?
  3. How do you operationalize deletion requests?
  4. Why are legal links release blockers?
  5. How do you keep policy text current during rapid iteration?

5.6 Hints in Layers

  • Hint 1: Build data inventory before writing any legal text.
  • Hint 2: Keep policy claims concrete and bounded.
  • Hint 3: Add legal URL and version checks to CI.
  • Hint 4: Tie every policy update to release notes.

5.7 Books That Will Help

Topic Book Chapter
Spec precision “Code Complete” Design/specification chapters
Process ownership “Clean Architecture” Responsibility boundaries
Iteration discipline “The Pragmatic Programmer” Source-of-truth patterns

6. Testing Strategy

  • Legal URL health checks.
  • Claim-to-evidence integrity validation.
  • Retention/deletion report checks.

7. Common Pitfalls & Debugging

Pitfall Symptom Solution
Template-only policies Claims mismatch runtime Build policy from data inventory
Broken legal links Submission blocked Add URL checks to release gates
Stale retention claims Trust and compliance risk Automate retention evidence reporting

8. Extensions & Challenges

  • Add locale-specific policy variants.
  • Add legal change approval workflow automation.
  • Add periodic policy drift audits.

9. Real-World Connections

  • Enterprise security review readiness
  • SaaS compliance operations
  • Cross-functional legal-engineering workflows

10. Resources

  • OpenAI Apps SDK: Submit your app
  • OpenAI Apps SDK: Security & privacy
  • OpenAI Help: Submitting apps to the directory

11. Self-Assessment Checklist

  • I can map each privacy claim to technical evidence.
  • I can run legal readiness checks automatically.
  • I can update legal artifacts safely during release changes.

12. Submission / Completion Criteria

Minimum Viable Completion

  • Public privacy and terms pages plus inventory baseline.

Full Completion

  • CI-enforced legal validation, claim-evidence mapping, and retention/deletion verification artifacts.