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nonlinear-xyznonlinear-xyz/factory-kit/skills/factory-db-schema-architect/SKILL.md

factory-db-schema-architect

Skill9 starsChanged 4 months agoMITView on GitHub

Use when designing or modifying database schemas, migrations, multi-tenant data models, or polymorphic table structures. Carries the factory's data-layer conventions — Drizzle with domain-partitioned schema modules, `_shared.ts` with `timestamps` helper and `pgTableCreator`, org-keyed FKs with cascade delete, JSONB envelope for non-query-driving data, polymorphic table patterns (shared base + variant tables), schema-derived type exports, ESLint Drizzle WHERE-enforcement, soft-delete mixin (Python). Produces schema files that fit the house style — not generic Postgres tables.

The file

We split this skill into the rules it gives an agent

11 rules. About 0 are common, 4 are distinctive, and 7 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈4

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 7

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Polymorphic?: If entities share a base type but diverge significantly (ICE vs BEV vehicles, individual vs business accounts), use the …

    line 14
  2. Very specific:

    Partition by domain?: Check src/server/db/schemas/:

    line 21
  3. Very specific:

    If _shared.ts exists with timestamps and pgTableCreator, reuse them

    line 22
  4. Distinctive:

    If not, create them as part of this work

    line 23
  5. Distinctive:

    Soft-delete or hard-delete?: Default to hard-delete (with cascade).

    line 26
  6. Very specific:

    ESLint Drizzle rules?: If eslint-plugin-drizzle isn't installed, recommend adding it for the WHERE enforcement on UPDATE/DELETE.

    line 36
  7. Very specific:

    Don't skip the org FK on domain tables: Every tenant-scoped table has it with onDelete: 'cascade'.

    line 108
  8. Very specific:

    Don't define entity types separately from the schema: Use $inferSelect / $inferInsert.

    line 110
  9. Distinctive:

    Don't put queryable data in JSONB: If something filters / sorts on it, it's a column.

    line 114
  10. Very specific:

    Don't add updatedAt manually: Use the timestamps spread from _shared.ts.

    line 116
  11. Distinctive:

    If the user asks to add a single column to an existing table, do it directly with a migration.

    line 120

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Apply the db-schema-architect specialist workflow. Design schemas grounded in the factory's data-layer conventions, not generic SQL. Load factory-data-layer and factory-stack through the host's skill capability when needed.

How to think (in order)

  1. What entities are in scope? Restate the request — name every entity, every relationship. If the user asks for "a customer model," check whether they mean (a) just customers, or (b) customers + addresses + contacts + .... Commit to the interpretation; flag the assumption.
  2. Multi-tenant key? Almost always yes. Every domain table gets orgId (or workspaceId / projectId) FK with onDelete: 'cascade'. If this is a shared-reference table (countries, states, vehicle types), call out that it's tenant-agnostic.
  3. Polymorphic? If entities share a base type but diverge significantly (ICE vs BEV vehicles, individual vs business accounts), use the shared-base + variant-tables pattern from factory-data-layer.md. Don't reach for nullable columns or discriminator: 'type'.
  4. JSONB or columns? For each field, ask: "Does anything query / sort / filter on this?"
    • Yes → real column
    • No, but it's structured → JSONB envelope (customAttributes, metadata, config)
    • No, and it's blob-shaped → external storage (S3) with a pointer column
  5. Partition by domain? Check src/server/db/schemas/:
    • If _shared.ts exists with timestamps and pgTableCreator, reuse them
    • If not, create them as part of this work
    • Pick / create the domain file (e.g. fleet.ts, payments.ts)
  6. Soft-delete or hard-delete? Default to hard-delete (with cascade). Use soft-delete when:
    • Regulatory requirement (audit history must persist)
    • User-facing "trash bin" UX
    • References across tenants where hard delete would break referential integrity
  7. Migration shape? drizzle-kit generate from the schema diff. Name the migration file:
    • Timestamps: <unix>_<verb_subject>.sql (preferred)
    • Or sequential: 000N_<verb_subject>.sql
    • Pick one convention per project and stick. Mixed naming is a factory-pitfalls.md entry.
  8. ESLint Drizzle rules? If eslint-plugin-drizzle isn't installed, recommend adding it for the WHERE enforcement on UPDATE/DELETE.

Reference: canonical schema file shape

// src/server/db/schemas/customers.ts
import { uuid, text, jsonb, pgEnum } from 'drizzle-orm/pg-core';
import { pgTable, timestamps } from './_shared';
import { organizations } from './auth';

export const customerStatus = pgEnum('customer_status', ['active', 'inactive', 'pending']);

export const customers = pgTable('customers', {
  id: uuid('id').defaultRandom().primaryKey(),
  orgId: uuid('org_id').references(() => organizations.id, { onDelete: 'cascade' }).notNull(),
  name: text('name').notNull(),
  email: text('email'),
  status: customerStatus('status').notNull().default('pending'),
  customAttributes: jsonb('custom_attributes').$type<Record<string, unknown>>().default({}),
  ...timestamps,
});

export type Customer = typeof customers.$inferSelect;
export type NewCustomer = typeof customers.$inferInsert;
// src/server/db/schemas/_shared.ts (create if missing)
import { pgTableCreator, timestamp } from 'drizzle-orm/pg-core';

export const pgTable = pgTableCreator((name) => `myapp_${name}`);

export const timestamps = {
  createdAt: timestamp('created_at').defaultNow().notNull(),
  updatedAt: timestamp('updated_at').defaultNow().notNull().$onUpdate(() => new Date()),
};

Output format

## Restated request
<one sentence — entities, relationships>

## Entities
- <entity>: <fields, relationships, tenancy key>

## Schema decisions
- Multi-tenant key: <orgId / workspaceId / N/A — why>
- Polymorphic: <yes/no — and shape>
- JSONB fields: <which fields, why>
- Soft-delete: <yes/no — why>
- Migration naming: <timestamps / sequential — flag if pre-existing convention differs>

## Files to create or modify
<bulleted with paths>

## Schema code
<actual Drizzle code, organized by file>

## Migration plan
<drizzle-kit generate command + resulting migration filename>

## ESLint check
- WHERE enforcement on UPDATE/DELETE: <enabled / recommend enabling>

## Open questions
<things the user should confirm>

What you do NOT do

  • Don't skip the org FK on domain tables. Every tenant-scoped table has it with onDelete: 'cascade'.
  • Don't put the whole schema in one file. Domain-partitioned modules.
  • Don't define entity types separately from the schema. Use $inferSelect / $inferInsert.
  • Don't allow nullable-column proliferation. Polymorphic? Use shared-base + variants.
  • Don't mix migration-file naming conventions within a project.
  • Don't run migrations at runtime. CI's job — see factory-deployment.md.
  • Don't put queryable data in JSONB. If something filters / sorts on it, it's a column.
  • Don't reach for raw SQL. Drizzle handles everything Postgres can do.
  • Don't add updatedAt manually. Use the timestamps spread from _shared.ts.

When the request is too small for this framework

If the user asks to add a single column to an existing table, do it directly with a migration. The framework is for new tables, new entities, or non-trivial schema evolution.

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