home / skills / thebushidocollective / han / graphql-schema-design

This skill helps you design scalable GraphQL schemas by applying best practices for types, pagination, directives, and versioning across services.

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---
name: graphql-schema-design
user-invocable: false
description: Use when designing GraphQL schemas with type system, SDL patterns, field design, pagination, directives, and versioning strategies for maintainable and scalable APIs.
allowed-tools: []
---

# GraphQL Schema Design

Apply GraphQL schema design principles to create well-structured,
maintainable, and scalable GraphQL APIs. This skill covers the type
system, Schema Definition Language (SDL), field design patterns,
pagination strategies, directives, and schema evolution techniques.

## Core Type System

### Object Types

Object types are the fundamental building blocks of GraphQL schemas.
Each object type represents a kind of object you can fetch from your
service, and what fields it has.

```graphql
type User {
  id: ID!
  username: String!
  email: String!
  createdAt: DateTime!
  posts: [Post!]!
  profile: Profile
}

type Post {
  id: ID!
  title: String!
  content: String!
  author: User!
  publishedAt: DateTime
  tags: [String!]!
}
```

### Interface Types

Interfaces define abstract types that multiple object types can
implement. Use interfaces when multiple types share common fields.

```graphql
interface Node {
  id: ID!
  createdAt: DateTime!
  updatedAt: DateTime!
}

interface Timestamped {
  createdAt: DateTime!
  updatedAt: DateTime!
}

type Article implements Node & Timestamped {
  id: ID!
  createdAt: DateTime!
  updatedAt: DateTime!
  title: String!
  content: String!
  author: User!
}

type Comment implements Node & Timestamped {
  id: ID!
  createdAt: DateTime!
  updatedAt: DateTime!
  text: String!
  author: User!
  post: Post!
}
```

### Union Types

Union types represent values that could be one of several object types.
Use unions when a field can return different types without shared
fields.

```graphql
union SearchResult = Article | User | Tag | Comment

type Query {
  search(query: String!): [SearchResult!]!
}

# Query example
query {
  search(query: "graphql") {
    __typename
    ... on Article {
      title
      content
    }
    ... on User {
      username
      email
    }
    ... on Tag {
      name
      count
    }
  }
}
```

### Enum Types

Enums define a specific set of allowed values for a field. Use enums
for fields with a fixed set of options to ensure type safety.

```graphql
enum UserRole {
  ADMIN
  MODERATOR
  USER
  GUEST
}

enum PostStatus {
  DRAFT
  PUBLISHED
  ARCHIVED
  DELETED
}

enum SortOrder {
  ASC
  DESC
}

type User {
  id: ID!
  role: UserRole!
  status: AccountStatus!
}

enum AccountStatus {
  ACTIVE
  SUSPENDED
  DEACTIVATED
}
```

### Input Types

Input types are used for complex arguments in queries and mutations.
They allow you to pass structured data as a single argument.

```graphql
input CreateUserInput {
  username: String!
  email: String!
  password: String!
  profile: UserProfileInput
}

input UserProfileInput {
  firstName: String
  lastName: String
  bio: String
  avatarUrl: String
}

input UpdatePostInput {
  title: String
  content: String
  status: PostStatus
  tags: [String!]
}

input PostFilterInput {
  status: PostStatus
  authorId: ID
  tags: [String!]
  createdAfter: DateTime
  createdBefore: DateTime
}

type Mutation {
  createUser(input: CreateUserInput!): User!
  updatePost(id: ID!, input: UpdatePostInput!): Post!
}

type Query {
  posts(filter: PostFilterInput, limit: Int): [Post!]!
}
```

## Custom Scalars

Custom scalars extend the built-in scalar types (String, Int, Float,
Boolean, ID) with domain-specific types.

```graphql
scalar DateTime
scalar EmailAddress
scalar URL
scalar JSON
scalar UUID
scalar PositiveInt
scalar Currency

type User {
  id: UUID!
  email: EmailAddress!
  website: URL
  createdAt: DateTime!
  metadata: JSON
  age: PositiveInt
}

type Product {
  id: ID!
  price: Currency!
  images: [URL!]!
}
```

## Directives

Directives provide a way to modify execution behavior or add metadata
to your schema.

```graphql
# Built-in directives
type Query {
  # Skip field if condition is true
  user(id: ID!): User @skip(if: $skipUser)

  # Include field only if condition is true
  posts: [Post!]! @include(if: $includePosts)
}

type Post {
  id: ID!
  title: String!
  # Mark field as deprecated with migration hint
  oldTitle: String @deprecated(reason: "Use 'title' instead")
}

# Custom directives
directive @auth(requires: UserRole!) on FIELD_DEFINITION
directive @rateLimit(max: Int!, window: Int!) on FIELD_DEFINITION
directive @cacheControl(
  maxAge: Int!
  scope: CacheScope = PUBLIC
) on FIELD_DEFINITION | OBJECT

enum CacheScope {
  PUBLIC
  PRIVATE
}

type Query {
  me: User @auth(requires: USER)
  adminPanel: AdminData @auth(requires: ADMIN)

  publicPosts: [Post!]!
    @cacheControl(maxAge: 300)
    @rateLimit(max: 100, window: 60)
}
```

## Nullable vs Non-Null Design

Carefully consider nullability in your schema design. Non-null fields
provide stronger guarantees but reduce flexibility.

```graphql
type User {
  # Required fields - will never be null
  id: ID!
  username: String!
  email: String!

  # Optional fields - may be null
  bio: String
  website: URL

  # Non-null list with nullable items
  # List itself will never be null, but items can be
  favoriteColors: [String]!

  # Nullable list with non-null items
  # List can be null, but if present, items won't be
  phoneNumbers: [String!]

  # Non-null list with non-null items
  # Neither list nor items will be null
  roles: [UserRole!]!

  # Optional relationship
  profile: Profile

  # Required relationship
  account: Account!
}
```

## Pagination Patterns

### Offset-Based Pagination

Simple pagination using limit and offset. Easy to implement but has
performance issues with large offsets.

```graphql
type Query {
  posts(limit: Int = 10, offset: Int = 0): PostsResult!
}

type PostsResult {
  posts: [Post!]!
  total: Int!
  hasMore: Boolean!
}

# Query example
query {
  posts(limit: 20, offset: 40) {
    posts {
      id
      title
    }
    total
    hasMore
  }
}
```

### Cursor-Based Pagination (Connections)

More efficient for large datasets and supports bidirectional
pagination. Based on Relay Connection specification.

```graphql
type Query {
  posts(
    first: Int
    after: String
    last: Int
    before: String
  ): PostConnection!
}

type PostConnection {
  edges: [PostEdge!]!
  pageInfo: PageInfo!
  totalCount: Int!
}

type PostEdge {
  node: Post!
  cursor: String!
}

type PageInfo {
  hasNextPage: Boolean!
  hasPreviousPage: Boolean!
  startCursor: String
  endCursor: String
}

# Query example
query {
  posts(first: 10, after: "Y3Vyc29yOjEw") {
    edges {
      cursor
      node {
        id
        title
      }
    }
    pageInfo {
      hasNextPage
      endCursor
    }
  }
}
```

## Mutation Design Patterns

### Input Object Pattern

Use input objects for mutations to allow for easier evolution and
better organization of arguments.

```graphql
type Mutation {
  createPost(input: CreatePostInput!): CreatePostPayload!
  updatePost(input: UpdatePostInput!): UpdatePostPayload!
  deletePost(input: DeletePostInput!): DeletePostPayload!
}

input CreatePostInput {
  title: String!
  content: String!
  authorId: ID!
  tags: [String!]
  publishedAt: DateTime
}

type CreatePostPayload {
  post: Post
  errors: [UserError!]
  success: Boolean!
}

type UserError {
  message: String!
  field: String
  code: String!
}

input UpdatePostInput {
  id: ID!
  title: String
  content: String
  status: PostStatus
}

type UpdatePostPayload {
  post: Post
  errors: [UserError!]
  success: Boolean!
}
```

## Error Handling in Schema

Design your schema to support both field-level and mutation-level
error handling.

```graphql
type Mutation {
  # Option 1: Union return type
  login(email: String!, password: String!): LoginResult!
}

union LoginResult = LoginSuccess | LoginError

type LoginSuccess {
  user: User!
  token: String!
  expiresAt: DateTime!
}

type LoginError {
  message: String!
  code: LoginErrorCode!
}

enum LoginErrorCode {
  INVALID_CREDENTIALS
  ACCOUNT_LOCKED
  EMAIL_NOT_VERIFIED
}

# Option 2: Payload with errors array
type Mutation {
  updateUser(input: UpdateUserInput!): UpdateUserPayload!
}

type UpdateUserPayload {
  user: User
  errors: [UserError!]
  success: Boolean!
}
```

## Schema Stitching and Federation Basics

### Schema Federation

Design schemas for federation by defining entities and extending types
across services.

```graphql
# User service
type User @key(fields: "id") {
  id: ID!
  username: String!
  email: String!
}

# Posts service
extend type User @key(fields: "id") {
  id: ID! @external
  posts: [Post!]!
}

type Post @key(fields: "id") {
  id: ID!
  title: String!
  content: String!
  author: User!
}

# Reviews service
extend type Post @key(fields: "id") {
  id: ID! @external
  reviews: [Review!]!
}

type Review {
  id: ID!
  rating: Int!
  comment: String
  post: Post!
}
```

## Versioning Strategies

### Field Deprecation

Mark fields as deprecated while maintaining backward compatibility.

```graphql
type User {
  id: ID!
  name: String! @deprecated(
    reason: "Use 'firstName' and 'lastName' instead"
  )
  firstName: String!
  lastName: String!

  email: String! @deprecated(
    reason: "Use 'primaryEmail' from ContactInfo"
  )
  contactInfo: ContactInfo!
}

type ContactInfo {
  primaryEmail: String!
  secondaryEmails: [String!]!
}
```

### Additive Changes

Add new fields and types without breaking existing queries.

```graphql
# Version 1
type Post {
  id: ID!
  title: String!
  content: String!
}

# Version 2 - Additive changes
type Post {
  id: ID!
  title: String!
  content: String!
  # New fields added
  summary: String
  readingTime: Int
  tags: [Tag!]!
}

# New type added
type Tag {
  id: ID!
  name: String!
  color: String
}
```

## Best Practices

1. **Use meaningful names**: Choose clear, descriptive names for types,
   fields, and arguments that reflect their purpose and domain
2. **Design for nullable fields**: Make fields nullable by default
   unless you can guarantee the value will always be present
3. **Prefer input objects**: Use input types for complex arguments in
   mutations to allow for easier evolution
4. **Implement pagination**: Always paginate list fields that could
   grow unbounded using cursor-based or offset-based patterns
5. **Use enums for fixed sets**: Define enums for fields with a
   limited set of possible values to ensure type safety
6. **Document your schema**: Add descriptions to types, fields, and
   arguments using GraphQL description syntax
7. **Version through deprecation**: Use @deprecated directive rather
   than removing fields to maintain backward compatibility
8. **Design mutations carefully**: Return payload types that include
   both the result and potential errors
9. **Keep schema flat**: Avoid deeply nested types that could lead to
   complex queries and N+1 problems
10. **Use interfaces wisely**: Define interfaces for shared fields
    across multiple types to enable polymorphic queries

## Common Pitfalls

1. **Over-fetching in schema design**: Creating fields that return
   entire objects when only specific data is needed
2. **Under-fetching**: Not providing enough related data, forcing
   clients to make multiple requests
3. **Circular dependencies**: Creating circular references between
   types without careful resolver design
4. **Breaking changes**: Removing or renaming fields without
   deprecation period, breaking existing clients
5. **No pagination**: Returning unbounded lists that can cause
   performance issues as data grows
6. **Inconsistent naming**: Using different conventions for similar
   fields across types
7. **Over-use of non-null**: Making too many fields non-null, reducing
   schema flexibility and resilience
8. **Missing error handling**: Not designing proper error handling in
   mutation payloads
9. **Ignoring N+1 problems**: Creating schema designs that inherently
   lead to N+1 query problems
10. **Poor input validation**: Not defining constraints on input types,
    leading to runtime validation issues

## When to Use This Skill

Use GraphQL schema design skills when:

- Designing a new GraphQL API from scratch
- Refactoring an existing GraphQL schema for better structure
- Adding new features to an existing schema
- Migrating from REST to GraphQL
- Implementing schema federation across microservices
- Optimizing schema for performance and maintainability
- Establishing schema design standards for a team
- Reviewing and improving schema design patterns
- Designing for long-term API evolution and versioning
- Creating reusable schema patterns and conventions

## Resources

- [GraphQL Specification](https://spec.graphql.org/) - Official
  GraphQL specification
- [GraphQL Best Practices](https://graphql.org/learn/best-practices/) -
  Official best practices guide
- [Apollo Schema Design Guide](https://www.apollographql.com/docs/apollo-server/schema/schema/)
  Schema design patterns
- [Relay Connection Specification](https://relay.dev/graphql/connections.htm) -
  Cursor-based pagination standard
- [GraphQL Schema Design Book](https://book.graphql.guide/) - In-depth
  schema design resource

Overview

This skill helps design clear, maintainable, and scalable GraphQL schemas focused on types, SDL patterns, field design, pagination, directives, and versioning. It provides practical guidance for object, interface, union, enum, input, and custom scalar design so APIs are predictable and evolvable. Use it to avoid common pitfalls and adopt patterns that support performance, federation, and safe schema evolution.

How this skill works

The skill inspects schema goals and recommends type system choices: when to use objects, interfaces, unions, enums, inputs, and custom scalars. It outlines field nullability, pagination (offset vs cursor), mutation payload patterns, directives for auth/cache/rate-limiting, and strategies for deprecation and additive changes. It also highlights federation and schema evolution tactics to keep services composable and backward compatible.

When to use it

  • Designing a new GraphQL API from scratch
  • Refactoring or reorganizing an existing schema
  • Adding features that affect types, relationships, or pagination
  • Migrating REST endpoints into a GraphQL layer
  • Preparing schemas for federation across microservices
  • Establishing team-wide schema design standards

Best practices

  • Choose meaningful, domain-oriented names for types, fields, and arguments
  • Make fields nullable by default unless presence can be guaranteed
  • Prefer input object types for mutation arguments to ease evolution
  • Always paginate potentially unbounded lists; prefer cursor-based for scale
  • Return payloads that include result and structured errors for mutations
  • Use @deprecated for field removal and add new fields instead of breaking changes

Example use cases

  • Modeling domain entities with interfaces and unions for polymorphic queries
  • Implementing cursor-based PostConnection for scalable feed pagination
  • Adding custom scalars (DateTime, Email, UUID) to enforce domain constraints
  • Defining @auth and @rateLimit directives to centralize access control and throttling
  • Designing mutation payloads with errors array and success flag for robust client handling
  • Extending types across services for federation using @key and extend patterns

FAQ

How do I choose between offset and cursor pagination?

Use offset for simple, low-volume lists and prototypes. Use cursor-based (connections) for large datasets, consistent ordering, and reliable next/previous navigation.

When should I mark a field non-null?

Mark non-null when you can guarantee the field will always be present; prefer nullable by default to avoid breaking clients and runtime errors.