Editing Openai/69111a25-dab4-8000-8929-8d5e16a9da88 (section)

=== Assistant: Absolutely — yes, I can do A through D in full. ===
Absolutely — yes, I can do A through D in full.
Here’s what that means in concrete terms for your Prototype Unsecured Credit Card Master Data Validation & Enforcement Process:

==== A self-contained Python FastAPI service that: ====
* Accepts JSON payloads of card records (POST /validate)
* Runs the rule set we established (Luhn, expiry, PCI, encryption, etc.)
* Returns a structured JSON response (pass/fail, list of rule results)
* Optionally logs validation outcomes to a CSV or database table
* Includes unit tests and Dockerfile for deployment

Deliverables:
* app/main.py (FastAPI app)
* app/validation.py (core rule logic)
* tests/test_validation.py (pytest)
* Dockerfile (container image build)
* README.md (run instructions)

==== A card_master.schema.json file (JSON Schema v2020-12) and equivalent Pydantic model class that enforces: ====
* Type safety (string, number, boolean)
* Required fields
* Regex constraints for expiry and masked formats
* Enum constraints for networks and tokenization providers
* Cross-field dependencies (expiry valid if month and year both valid)

==== A short, professional Runbook in document format that outlines: ====
* Common validation failure codes and meanings
* Steps for remediation (re-tokenization, encryption key check, BIN lookup, etc.)
* Escalation paths (Security, Data Stewardship, IT Ops)
* Example ticket templates (for ServiceNow/JIRA)
* SLA expectations

==== A review of your actual validation CSV output — for each record, I’ll: ====
* Flag test/demo cards
* Mark any that appear production-eligible but failed a rule
* Recommend per-record actions (e.g. "Mark TEST", "Request re-tokenization", "OK to retain")

Before I begin, can you please confirm two short details:
# Do you want all four outputs (A–D) bundled into a single ZIP package (with source code + runbook + reports)?
# For the microservice, would you prefer: - 🧩 Lightweight prototype mode (runs locally, no DB, saves results to CSV) - 💾 Production-ready stub (includes database layer + API auth + Docker Compose file)?

Once you confirm those, I’ll generate everything (including downloadable files).