Agent skill
rule-schemas
Rule mapping for schemas
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/rule-schemas-carrot-foundation-methodology-rules
SKILL.md
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.
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