rule-schemas

Development

Rule mapping for schemas

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Source SKILL.md: https://github.com/majiayu000/claude-skill-registry/blob/HEAD/skills/development/rule-schemas-carrot-foundation-methodology-rules/SKILL.md

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Rule schemas

Apply this rule whenever work touches:

*.ts

Zod is the runtime validation library for this project. Schemas serve a dual purpose: they validate data at runtime boundaries and provide the canonical type definition via z.infer.

Schema definition

Define schemas close to the types they describe. A common pattern is to export both from the same file:

import { z } from 'zod';

export const VehicleSchema = z.object({
  plate: z.string().min(7),
  weightKg: z.number().positive(),
  type: z.enum(['truck', 'van', 'car']),
});

export type Vehicle = z.infer<typeof VehicleSchema>;

Never create a separate interface Vehicle that duplicates the schema shape.

Validation strategy

Choose the right parse method based on the trust level of the data:

// External input (API payload, S3 object, SQS message) - handle errors
const result = VehicleSchema.safeParse(rawPayload);
if (!result.success) {
  logger.warn('Invalid vehicle payload', result.error.flatten());
  return { error: 'INVALID_INPUT' };
}
const vehicle = result.data;

// Internal data (already validated upstream) - let it throw
const vehicle = VehicleSchema.parse(trustedData);

Schema composition

Reuse schemas through composition rather than copy-pasting fields:

const BaseDocumentSchema = z.object({
  id: z.string().uuid(),
  createdAt: z.string().datetime(),
});

const CertificateSchema = BaseDocumentSchema.extend({
  issuer: z.string(),
  validUntil: z.string().datetime(),
});

Test data generation

Use zocker and the shared testing utilities to generate test data from schemas:

import { createStubFromSchema } from '@carrot-fndn/shared/testing';

const stubVehicle = createStubFromSchema(VehicleSchema);

This ensures test data always conforms to the current schema shape and evolves automatically when the schema changes.