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Data modeling

Skill MartinOlivero/saas-builder/skills/data-modeling

Build a complete, secure SaaS end to end in Claude Code: prevention-first security (not audit), real Stripe payments (not just a catalog), and 15 lifecycle skills. Pairs with Superpowers — needs nothing else.

Install
npx -y skills add MartinOlivero/saas-builder --skill data-modeling

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This skill should be used when designing a database schema, modeling data, choosing a database, planning migrations, or setting up multi-tenancy for a SaaS. Trigger phrases include "design the database", "model this data", "what database should I use", "schema for", "multi-tenant", "tenant isolation", "add an index", "how do I migrate", "SQL or NoSQL", "Postgres schema", "row level security", "RLS". It defaults to Postgres, models multi-tenancy safely, and enforces migration and indexing discipline.

SKILL.md

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Data Modeling

This skill designs the schema your product runs on, and gets multi-tenant isolation right — the mistake that, when wrong, leaks one customer's data to another.

Analogy: the schema is the foundation and load-bearing walls of a house. You can repaint and rearrange furniture later cheaply; moving a load-bearing wall after move-in is expensive and dangerous. Get the structure right before building on it.

Discovery (max 3 questions, only if unknown)

  1. Is this multi-tenant (multiple orgs/customers sharing the app) or single-tenant?
  2. Is the data mostly relational (users, orders, invoices) or document-like/flexible?
  3. Are you on Supabase, Neon, or another Postgres host — or undecided?

Step 1 — Choose the database

Postgres by default — relational integrity, JSONB for flexible fields, full-text search, and it scales far. Don't reach for NoSQL without a proven document/scale reason. Every option below runs Postgres underneath, so the methodology in this skill (tenant_id + RLS, indexing, migrations) is identical regardless of host. Pick the host by how you're building:

  • InsForgeagentic-native. Built so an AI coding agent provisions the DB, runs migrations, sets RLS, and debugs through MCP, without you touching a dashboard. The natural fit when you build with an agent — which is exactly how this plugin runs. Batteries-included (Postgres + auth + RLS + storage + functions), open source. (Its published benchmarks claim faster/cheaper agent task completion vs Supabase — note those are first-party numbers, and it's a younger project (~5k⭐) than Supabase.)
  • Supabasemature ecosystem. Batteries-included (Auth + RLS + Realtime + storage), RLS battle-tested at scale, huge community and docs (~104k⭐). The safe default when ecosystem maturity matters more than agent-native tooling.
  • Neon — serverless Postgres with branching/autoscaling; great for preview-per-PR databases.
  • Redis only for cache/sessions/real-time; Elasticsearch only for heavy full-text search.

Decision rule: building inside an AI agent and want it to own the backend end to end → InsForge. Want the largest, most-proven ecosystem → Supabase. Either way the schema design below is the same.

Step 2 — Model multi-tenancy (the critical decision)

Default to a shared schema with a tenant_id (org_id) column on every tenant-scoped table + Row-Level Security. Graduate to schema-per-tenant or DB-per-tenant only when a large enterprise customer demands hard isolation/compliance. Don't start there — it multiplies ops cost.

Make RLS airtight:

  • ENABLE ROW LEVEL SECURITY and FORCE ROW LEVEL SECURITY on every tenant table.
  • Set tenant context per request inside the transaction: SET LOCAL app.current_tenant = '...' — so pooled connections can't leak state between requests.
  • The application DB role must have neither SUPERUSER nor BYPASSRLS — otherwise RLS is silently skipped and isolation is an illusion.
  • RLS is the backstop for the app-layer tenant_id checks in the auth skill — defense in depth.

Step 3 — Schema discipline

  • Normalize to 3NF by default. Denormalize only for a measured read hot-path.
  • IDs: UUID/ULID for public-facing identifiers; bigint identity for internal PKs.
  • Index every foreign key and every column you filter/sort/join on. Postgres does not auto-index FKs. For tenant tables, lead a composite index with tenant_id, e.g. (tenant_id, created_at).
  • Timestamps: created_at / updated_at as timestamptz in UTC. Prefer soft delete (deleted_at) for user-facing data.
  • Push invariants into the schema: NOT NULL, CHECK, UNIQUE, FK constraints — not just app code.

Step 4 — Migrations

  • All schema changes go through versioned, forward-only migration files in source control (Supabase migrations, Prisma Migrate, or Drizzle).
  • Never edit the production DB by hand. Every change is a reviewable, replayable migration.
  • Delegation & fallback: if the InsForge skills are installed (npx skills add https://github.com/insforge/agent-skills), let insforge-cli apply migrations/RLS and insforge-debug diagnose issues — the agent operates the backend directly. If they're not, apply migrations through your host's CLI (Supabase / Drizzle / Prisma). This skill always owns the design; never block on a missing skill.

Handoff

The schema here backs the api-design resources and the auth permission model. Pass the tenant strategy to both so endpoints and policies scope correctly.

Output

Deliver: the DB choice with reason, the multi-tenancy strategy, the table definitions (DDL) with constraints and indexes, the RLS policies if multi-tenant, and the first migration file.

Reference

PostgreSQL docs (RLS, indexing), supabase/supabase (~104k⭐), insforge/insforge (~5k⭐, agentic-native), AWS "Multi-tenant data isolation with Postgres RLS", PlanetScale "Approaches to tenancy in Postgres".

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