Intake Schema & Validation Blueprint Generator
Generate a complete intake data model with validations, PII flags, consent keys, and DB-ready names tailored to your service line.
Prompt Overview
Featured AI Partner
Tips For You
- Start with your most common engagement types, not edge cases. - Mark every field that drives pricing or eligibility. - Keep enumerations small at launch; expand later based on analytics.
From Operations TeamNexusAi TechnologyProblem It Solves
Prevents incomplete submissions, incompatible fields, and ad-hoc spreadsheets by defining a robust, normalized schema and validation rules up front.
Complete JSON Schemas
Generates copy-paste field definitions with validations.
PII/Consent Flags
Clearly tags sensitive fields and consent capture.
RLS Intent Map
Outlines record ownership and reviewer access.
Indexing Hints
Recommends keys and indexes for speed and integrity.
AI Prompt Instructions
Act as: A senior solutions architect for professional services onboarding who specializes in data modeling, regulated data capture, and Supabase/Postgres design.
Why this task matters: Service intake often misses required details and stores PII insecurely. A rigorously defined schema with validations, consent structures, and mapping to a relational database prevents rework and compliance issues.
Important boundaries: Assume Supabase Postgres + Auth. Use ISO formats for dates/times. Mark any PII/PHI fields. Include consent and retention fields. Keep naming snake_case. Avoid over-normalization that harms UX.
User inputs (provide or ask me for them if missing):
1) Industry and service type(s)
2) Required documents list and max sizes
3) Regulatory constraints (e.g., GDPR, HIPAA, SEC)
4) Languages/locales needed
5) Distinct user roles (client, intake reviewer, admin)
6) Key downstream systems (billing, CRM)
Objectives:
- Produce an entity-field blueprint with types, validations, and conditional logic
- Identify mandatory vs optional fields and cross-field dependencies
- Tag PII/PHI and define consent collection fields
- Map to a Supabase-ready table design with RLS assumptions
Analysis workflow:
1) Clarify industry-specific data and regulatory must-haves
2) Draft entities: client_profile, engagement, intake_submission, file_upload, consent, status_event
3) For each field: name, label, type, regex/range, required, conditional_on, pii_flag, example_value
4) Define enumerations and normalization boundaries
5) Outline RLS patterns by role and record ownership
6) Propose indexing strategy, unique constraints, and foreign keys
Required output format:
- Section A: High-level ERD notes (bulleted)
- Section B: JSON Schema for each entity and fields with validations
- Section C: Supabase table definitions (DDL outline, not full SQL)
- Section D: RLS policy intentions per table
- Section E: Consent and retention matrix
Quality controls:
- Every required document has file_type, size_limit_mb, virus_scan=true, storage_path pattern
- All date fields specify timezone and format
- No ambiguous free-text where controlled lists are safer
Verification checklist:
- Can a single client manage multiple engagements?
- Are consent versions and timestamps captured?
- Are status_events append-only with actor and reason?
Final instruction: Produce the full blueprint with clear headings and compact, copy-pastable JSON for schemas. Ask 3 clarification questions first if anything is ambiguous.
Expected Outcome
Section A (ERD Notes): client_profile 1..* engagement; engagement 1..1 intake_submission; intake_submission 1..* file_upload; intake_submission 1..* status_event; client_profile 1..* consent. Section B (JSON Schema excerpt): {"client_profile":{"fields":[{"name":"first_name","type":"text","required":true,"pii":true},{"name":"email","type":"email","required":true,"unique":true}]}}
Implementation Journey
Draft the schema in ChatGPT
Open ChatGPT and paste the prompt with your industry, required docs, roles, and constraints. Request the ERD notes, JSON Schemas, and RLS intentions. Expect a structured blueprint you can copy to your project docs.
15 minTranslate to Supabase structures
Use the JSON Schema to create tables in Supabase. Create tables client_profile, engagement, intake_submission, file_upload, consent, status_event, and apply constraints and indexes suggested by the blueprint.
25 minField test with a sample submission
In Supabase, insert a test client and submission. Verify required fields, enumerations, and foreign keys behave as expected. Note any missing validations to refine in ChatGPT.
20 min
