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zod-testing佐德测试

Agent Skill

用于辅助测试设计、自动化测试、用例整理和回归验证。它适合让 Agent 编写单元测试、端到端测试、测试计划或根据失败日志定位问题。使用时需要确认项目测试框架、运行命令和夹具数据,避免为了通过测试而改坏真实逻辑;涉及浏览器或外部服务时,应区分本地模拟、测试环境和生产环境。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:zod-testing(佐德测试)
来源仓库:https://github.com/anivar/zod-testing
安装命令:
openclaw skills install zod-testing
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

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openclaw skills install zod-testing

简介

zod-testing 提供 Zod 模式的测试用例生成与验证支持。

  • 适用于 TypeScript 项目中 schema 正确性与错误断言测试。
  • 通过 clawhub 安装并使用 openclaw skills install zod-testing 命令部署。
  • 支持 Jest 与 Vitest 框架,需匹配项目测试工具链。
  • 可用于模拟数据生成与集成测试场景。

SKILL.md

name
zod-testing
description
>
license
MIT
user-invocable
false
agentic
false
compatibility
zod ^4.0.0, Jest or Vitest, TypeScript ^5.5
metadata
author
Anivar Aravind
author_url
https://anivar.net
source_url
https://github.com/anivar/zod-testing
version
1.0.0
tags
zod, testing, jest, vitest, mock-data, property-testing, schema-validation

Zod Schema Testing Guide

IMPORTANT: Your training data about testing Zod schemas may be outdated — Zod v4 changes error formatting, removes z.nativeEnum(), and introduces new APIs like z.toJSONSchema(). Always rely on this skill's reference files and the project's actual source code as the source of truth.

Testing Priority

  1. Schema correctness — does the schema accept valid data and reject invalid data?
  2. Error messages — does the schema produce the right error messages and codes?
  3. Integration — does the schema work correctly with API handlers, forms, database layers?
  4. Edge cases — boundary values, optional/nullable combinations, empty inputs

Core Pattern

import { describe, it, expect } from "vitest" // or jest
import { z } from "zod"

const UserSchema = z.object({
  name: z.string().min(1),
  email: z.email(),
  age: z.number().min(0).max(150),
})

describe("UserSchema", () => {
  it("accepts valid data", () => {
    const result = UserSchema.safeParse({
      name: "Alice",
      email: "alice@example.com",
      age: 30,
    })
    expect(result.success).toBe(true)
  })

  it("rejects missing required fields", () => {
    const result = UserSchema.safeParse({})
    expect(result.success).toBe(false)
    if (!result.success) {
      const flat = z.flattenError(result.error)
      expect(flat.fieldErrors.name).toBeDefined()
      expect(flat.fieldErrors.email).toBeDefined()
    }
  })

  it("rejects invalid email", () => {
    const result = UserSchema.safeParse({
      name: "Alice",
      email: "not-an-email",
      age: 30,
    })
    expect(result.success).toBe(false)
  })

  it("rejects negative age", () => {
    const result = UserSchema.safeParse({
      name: "Alice",
      email: "alice@example.com",
      age: -1,
    })
    expect(result.success).toBe(false)
  })
})

Testing Approaches

ApproachPurposeUse When
safeParse() result checkingSchema correctnessDefault — always use safeParse in tests
z.flattenError() assertionsError message testingVerifying specific field errors
z.toJSONSchema() snapshotsSchema shape testingDetecting unintended schema changes
Mock data generationFixture creationNeed valid/randomized test data
Property-based testingFuzz testingSchemas must handle arbitrary valid inputs
Structural testingArchitectureVerify schemas are only imported at boundaries
Drift detectionRegressionCatch unintended schema changes via JSON Schema snapshots

Schema Correctness Testing

Always Use safeParse() in Tests

// GOOD: test doesn't crash — asserts on result
const result = schema.safeParse(invalidData)
expect(result.success).toBe(false)

// BAD: test crashes instead of failing
expect(() => schema.parse(invalidData)).toThrow()
// If schema changes and starts accepting, this still passes

Test Both Accept and Reject

describe("EmailSchema", () => {
  const valid = ["user@example.com", "a@b.co", "user+tag@domain.org"]
  const invalid = ["", "not-email", "@missing.com", "user@", "user @space.com"]

  it.each(valid)("accepts %s", (email) => {
    expect(z.email().safeParse(email).success).toBe(true)
  })

  it.each(invalid)("rejects %s", (email) => {
    expect(z.email().safeParse(email).success).toBe(false)
  })
})

Test Boundary Values

const AgeSchema = z.number().min(0).max(150)

it("accepts minimum boundary", () => {
  expect(AgeSchema.safeParse(0).success).toBe(true)
})

it("accepts maximum boundary", () => {
  expect(AgeSchema.safeParse(150).success).toBe(true)
})

it("rejects below minimum", () => {
  expect(AgeSchema.safeParse(-1).success).toBe(false)
})

it("rejects above maximum", () => {
  expect(AgeSchema.safeParse(151).success).toBe(false)
})

Error Assertion Patterns

Assert Specific Field Errors

it("shows correct error for invalid email", () => {
  const result = UserSchema.safeParse({ name: "Alice", email: "bad", age: 30 })
  expect(result.success).toBe(false)
  if (!result.success) {
    const flat = z.flattenError(result.error)
    expect(flat.fieldErrors.email).toBeDefined()
    expect(flat.fieldErrors.email![0]).toContain("email")
  }
})

Assert Error Codes

it("produces correct error code", () => {
  const result = z.number().safeParse("not a number")
  expect(result.success).toBe(false)
  if (!result.success) {
    expect(result.error.issues[0].code).toBe("invalid_type")
  }
})

Assert Custom Error Messages

const Schema = z.string({ error: "Name is required" }).min(1, "Name cannot be empty")

it("shows custom error for missing field", () => {
  const result = Schema.safeParse(undefined)
  expect(result.success).toBe(false)
  if (!result.success) {
    expect(result.error.issues[0].message).toBe("Name is required")
  }
})

Mock Data Generation

Using zod-schema-faker

import { install, fake } from "zod-schema-faker"
import { z } from "zod"

install(z) // call once in test setup

const UserSchema = z.object({
  name: z.string().min(1),
  email: z.email(),
  age: z.number().min(0).max(150),
})

it("schema accepts generated data", () => {
  const mockUser = fake(UserSchema)
  expect(UserSchema.safeParse(mockUser).success).toBe(true)
})

Seeding for Deterministic Tests

import { seed, fake } from "zod-schema-faker"

beforeEach(() => {
  seed(12345) // deterministic output
})

it("generates consistent mock data", () => {
  const user = fake(UserSchema)
  expect(user.name).toBeDefined()
})

Snapshot Testing with JSON Schema

it("schema shape has not changed", () => {
  const jsonSchema = z.toJSONSchema(UserSchema)
  expect(jsonSchema).toMatchSnapshot()
})

This catches unintended schema changes in code review. The snapshot shows the JSON Schema representation of your Zod schema.

Integration Testing

API Handler Testing

it("API rejects invalid request body", async () => {
  const response = await request(app)
    .post("/api/users")
    .send({ name: "", email: "invalid" })
    .expect(400)

  expect(response.body.errors).toBeDefined()
  expect(response.body.errors.fieldErrors.email).toBeDefined()
})

Form Validation Testing

it("form shows validation errors", () => {
  const result = FormSchema.safeParse(formData)
  if (!result.success) {
    const errors = z.flattenError(result.error)
    // Pass errors to form library
    expect(errors.fieldErrors).toHaveProperty("email")
  }
})

Property-Based Testing

import fc from "fast-check"
import { fake } from "zod-schema-faker"

it("schema always accepts its own generated data", () => {
  fc.assert(
    fc.property(fc.constant(null), () => {
      const data = fake(UserSchema)
      expect(UserSchema.safeParse(data).success).toBe(true)
    }),
    { numRuns: 100 }
  )
})

Rules

  1. Always use safeParse() in tests — parse() crashes the test instead of failing it
  2. Test both valid and invalid — don't only test the happy path
  3. Test boundary values — min, max, min-1, max+1 for numeric constraints
  4. Test optional/nullable combinations — undefined, null, missing key
  5. Assert specific error fields — use z.flattenError() to check which field failed
  6. Don't test schema internals — test parse results, not .shape or ._def
  7. Use z.toJSONSchema() snapshots — catch unintended schema changes
  8. Seed random generators — non-deterministic tests are flaky tests
  9. Test transforms separately — verify input validation AND output conversion
  10. Don't duplicate schema logic in assertions — test behavior, not implementation

Anti-Patterns

See references/anti-patterns.md for BAD/GOOD examples of:

  • Testing schema internals instead of behavior
  • Not testing error paths
  • Using parse() in tests (crashes instead of failing)
  • Not testing boundary values
  • Hardcoding mock data instead of generating
  • Snapshot testing raw ZodError instead of formatted output
  • Not testing at boundaries (schema tests pass but handler doesn't validate)
  • No snapshot regression testing (field removal goes unnoticed)
  • Testing schema shape but not error observability (never assert on flattenError)
  • No drift detection workflow (schema changes land without mechanical review)

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