graphql
GraphQL gives clients exactly the data they need - no more, no less. One endpoint, typed schema, introspection. But the flexibility that makes it powerful also makes it dangerous. Without proper controls, clients can craft queries that bring down your server.
About this skill
This skill transforms the AI agent's internal model to adopt the persona of a highly experienced GraphQL API developer. The agent will respond and reason from the perspective of someone who has built, scaled, and troubleshooted complex GraphQL APIs, intimately familiar with common pitfalls like the N+1 query problem, inefficient data fetching, and security vulnerabilities due to deep nesting. It emphasizes understanding the inherent power and potential dangers of GraphQL, advocating for best practices like DataLoader implementation and query depth limiting. This skill is designed to enable the AI agent to provide expert-level advice, troubleshoot issues, design robust schemas, and anticipate performance bottlenecks in GraphQL contexts.
Best use case
Getting expert advice on GraphQL API design and architecture. Troubleshooting performance issues in existing GraphQL implementations. Designing secure and scalable GraphQL schemas. Understanding the trade-offs and best practices for GraphQL development. Reviewing GraphQL queries for efficiency and potential problems. Educating on advanced GraphQL concepts (e.g., DataLoader, query batching).
GraphQL gives clients exactly the data they need - no more, no less. One endpoint, typed schema, introspection. But the flexibility that makes it powerful also makes it dangerous. Without proper controls, clients can craft queries that bring down your server.
The AI agent will provide highly informed, practical, and nuanced advice on GraphQL topics, reflecting the experience of a senior developer. Its responses will anticipate common problems, suggest robust solutions, and emphasize best practices for building scalable and secure GraphQL APIs.
Practical example
Example input
I'm designing a new GraphQL API for an e-commerce platform. How should I structure my schema to avoid the N+1 problem when fetching product details with their associated reviews and seller information? What security considerations should I keep in mind?
Example output
As someone who's tackled large-scale GraphQL APIs, I can tell you the N+1 problem is a killer. For your e-commerce platform, you absolutely need to implement **DataLoader** for batching requests to avoid hammering your backend. When a client requests products and their reviews, DataLoader can fetch all necessary reviews in a single batch query, then correctly associate them. For security, definitely implement **query depth limiting** and **query complexity analysis** to prevent malicious or accidental denial-of-service attacks from deeply nested or overly complex queries. Also, consider **rate limiting** and proper **authentication/authorization** at the resolver level to ensure users only access data they're permitted to see. Never expose sensitive internal identifiers directly.
When to use this skill
- When you need an AI agent to act as a subject matter expert for GraphQL.
- When seeking guidance on optimizing GraphQL API performance.
- When designing new GraphQL services or refactoring existing ones.
- When debugging complex GraphQL queries or server-side resolvers.
When not to use this skill
- When the task is unrelated to GraphQL development or API design.
- When simple data fetching or basic API interaction is required without needing expert consultation.
- When the agent's general knowledge is sufficient, and an expert persona is unnecessary overhead.
- When you need the agent to directly execute GraphQL queries or interact with GraphQL endpoints (this skill focuses on expert reasoning, not execution).
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/graphql/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How graphql Compares
| Feature / Agent | graphql | Standard Approach |
|---|---|---|
| Platform Support | Claude | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | easy | N/A |
Frequently Asked Questions
What does this skill do?
GraphQL gives clients exactly the data they need - no more, no less. One endpoint, typed schema, introspection. But the flexibility that makes it powerful also makes it dangerous. Without proper controls, clients can craft queries that bring down your server.
Which AI agents support this skill?
This skill is designed for Claude.
How difficult is it to install?
The installation complexity is rated as easy. You can find the installation instructions above.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# GraphQL
GraphQL gives clients exactly the data they need - no more, no less. One
endpoint, typed schema, introspection. But the flexibility that makes it
powerful also makes it dangerous. Without proper controls, clients can
craft queries that bring down your server.
This skill covers schema design, resolvers, DataLoader for N+1 prevention,
federation for microservices, and client integration with Apollo/urql.
Key insight: GraphQL is a contract. The schema is the API documentation.
Design it carefully.
2025 lesson: GraphQL isn't always the answer. For simple CRUD, REST is
simpler. For high-performance public APIs, REST with caching wins. Use
GraphQL when you have complex data relationships and diverse client needs.
## Principles
- Schema-first design - the schema is the contract
- Prevent N+1 queries with DataLoader
- Limit query depth and complexity
- Use fragments for reusable selections
- Mutations should be specific, not generic update operations
- Errors are data - use union types for expected failures
- Nullability is meaningful - design it intentionally
## Capabilities
- graphql-schema-design
- graphql-resolvers
- graphql-federation
- graphql-subscriptions
- graphql-dataloader
- graphql-codegen
- apollo-server
- apollo-client
- urql
## Scope
- database-queries -> postgres-wizard
- authentication -> authentication-oauth
- rest-api-design -> backend
- websocket-infrastructure -> backend
## Tooling
### Server
- @apollo/server - When: Apollo Server v4 Note: Most popular GraphQL server
- graphql-yoga - When: Lightweight alternative Note: Good for serverless
- mercurius - When: Fastify integration Note: Fast, uses JIT
### Client
- @apollo/client - When: Full-featured client Note: Caching, state management
- urql - When: Lightweight alternative Note: Smaller, simpler
- graphql-request - When: Simple requests Note: Minimal, no caching
### Tools
- graphql-codegen - When: Type generation Note: Essential for TypeScript
- dataloader - When: N+1 prevention Note: Batches and caches
## Patterns
### Schema Design
Type-safe schema with proper nullability
**When to use**: Designing any GraphQL API
# SCHEMA DESIGN:
"""
The schema is your API contract. Design nullability
intentionally - non-null fields must always resolve.
"""
type Query {
# Non-null - will always return user or throw
user(id: ID!): User!
# Nullable - returns null if not found
userByEmail(email: String!): User
# Non-null list with non-null items
users(limit: Int = 10, offset: Int = 0): [User!]!
# Search with pagination
searchUsers(
query: String!
first: Int
after: String
): UserConnection!
}
type Mutation {
# Input types for complex mutations
createUser(input: CreateUserInput!): CreateUserPayload!
updateUser(id: ID!, input: UpdateUserInput!): UpdateUserPayload!
deleteUser(id: ID!): DeleteUserPayload!
}
type Subscription {
userCreated: User!
messageReceived(roomId: ID!): Message!
}
# Input types
input CreateUserInput {
email: String!
name: String!
role: Role = USER
}
input UpdateUserInput {
email: String
name: String
role: Role
}
# Payload types (for errors as data)
type CreateUserPayload {
user: User
errors: [Error!]!
}
union UpdateUserPayload = UpdateUserSuccess | NotFoundError | ValidationError
type UpdateUserSuccess {
user: User!
}
# Enums
enum Role {
USER
ADMIN
MODERATOR
}
# Types with relationships
type User {
id: ID!
email: String!
name: String!
role: Role!
posts(limit: Int = 10): [Post!]!
createdAt: DateTime!
}
type Post {
id: ID!
title: String!
content: String!
author: User!
comments: [Comment!]!
published: Boolean!
}
# Pagination (Relay-style)
type UserConnection {
edges: [UserEdge!]!
pageInfo: PageInfo!
totalCount: Int!
}
type UserEdge {
node: User!
cursor: String!
}
type PageInfo {
hasNextPage: Boolean!
hasPreviousPage: Boolean!
startCursor: String
endCursor: String
}
### DataLoader for N+1 Prevention
Batch and cache database queries
**When to use**: Resolving relationships
# DATALOADER:
"""
Without DataLoader, fetching 10 posts with authors
makes 11 queries (1 for posts + 10 for each author).
DataLoader batches into 2 queries.
"""
import DataLoader from 'dataloader';
// Create loaders per request
function createLoaders(db) {
return {
userLoader: new DataLoader(async (ids) => {
// Single query for all users
const users = await db.user.findMany({
where: { id: { in: ids } }
});
// Return in same order as ids
const userMap = new Map(users.map(u => [u.id, u]));
return ids.map(id => userMap.get(id) || null);
}),
postsByAuthorLoader: new DataLoader(async (authorIds) => {
const posts = await db.post.findMany({
where: { authorId: { in: authorIds } }
});
// Group by author
const postsByAuthor = new Map();
posts.forEach(post => {
const existing = postsByAuthor.get(post.authorId) || [];
postsByAuthor.set(post.authorId, [...existing, post]);
});
return authorIds.map(id => postsByAuthor.get(id) || []);
})
};
}
// Attach to context
const server = new ApolloServer({
typeDefs,
resolvers,
});
app.use('/graphql', expressMiddleware(server, {
context: async ({ req }) => ({
db,
loaders: createLoaders(db),
user: req.user
})
}));
// Use in resolvers
const resolvers = {
Post: {
author: (post, _, { loaders }) => {
return loaders.userLoader.load(post.authorId);
}
},
User: {
posts: (user, _, { loaders }) => {
return loaders.postsByAuthorLoader.load(user.id);
}
}
};
### Apollo Client Caching
Normalized cache with type policies
**When to use**: Client-side data management
# APOLLO CLIENT CACHING:
"""
Apollo Client normalizes responses into a flat cache.
Configure type policies for custom cache behavior.
"""
import { ApolloClient, InMemoryCache } from '@apollo/client';
const cache = new InMemoryCache({
typePolicies: {
Query: {
fields: {
// Paginated field
users: {
keyArgs: ['query'], // Cache separately per query
merge(existing = { edges: [] }, incoming, { args }) {
// Append for infinite scroll
if (args?.after) {
return {
...incoming,
edges: [...existing.edges, ...incoming.edges]
};
}
return incoming;
}
}
}
},
User: {
keyFields: ['id'], // How to identify users
fields: {
fullName: {
read(_, { readField }) {
// Computed field
return `${readField('firstName')} ${readField('lastName')}`;
}
}
}
}
}
});
const client = new ApolloClient({
uri: '/graphql',
cache,
defaultOptions: {
watchQuery: {
fetchPolicy: 'cache-and-network'
}
}
});
// Queries with hooks
import { useQuery, useMutation } from '@apollo/client';
const GET_USER = gql`
query GetUser($id: ID!) {
user(id: $id) {
id
name
email
}
}
`;
function UserProfile({ userId }) {
const { data, loading, error } = useQuery(GET_USER, {
variables: { id: userId }
});
if (loading) return <Spinner />;
if (error) return <Error message={error.message} />;
return <div>{data.user.name}</div>;
}
// Mutations with cache updates
const CREATE_USER = gql`
mutation CreateUser($input: CreateUserInput!) {
createUser(input: $input) {
user {
id
name
email
}
errors {
field
message
}
}
}
`;
function CreateUserForm() {
const [createUser, { loading }] = useMutation(CREATE_USER, {
update(cache, { data: { createUser } }) {
// Update cache after mutation
if (createUser.user) {
cache.modify({
fields: {
users(existing = []) {
const newRef = cache.writeFragment({
data: createUser.user,
fragment: gql`
fragment NewUser on User {
id
name
email
}
`
});
return [...existing, newRef];
}
}
});
}
}
});
}
### Code Generation
Type-safe operations from schema
**When to use**: TypeScript projects
# GRAPHQL CODEGEN:
"""
Generate TypeScript types from your schema and operations.
No more manually typing query responses.
"""
# Install
npm install -D @graphql-codegen/cli
npm install -D @graphql-codegen/typescript
npm install -D @graphql-codegen/typescript-operations
npm install -D @graphql-codegen/typescript-react-apollo
# codegen.ts
import type { CodegenConfig } from '@graphql-codegen/cli';
const config: CodegenConfig = {
schema: 'http://localhost:4000/graphql',
documents: ['src/**/*.graphql', 'src/**/*.tsx'],
generates: {
'./src/generated/graphql.ts': {
plugins: [
'typescript',
'typescript-operations',
'typescript-react-apollo'
],
config: {
withHooks: true,
withComponent: false
}
}
}
};
export default config;
# Run generation
npx graphql-codegen
# Usage - fully typed!
import { useGetUserQuery, useCreateUserMutation } from './generated/graphql';
function UserProfile({ userId }: { userId: string }) {
const { data, loading } = useGetUserQuery({
variables: { id: userId } // Type-checked!
});
// data.user is fully typed
return <div>{data?.user?.name}</div>;
}
### Error Handling with Unions
Expected errors as data, not exceptions
**When to use**: Operations that can fail in expected ways
# ERRORS AS DATA:
"""
Use union types for expected failure cases.
GraphQL errors are for unexpected failures.
"""
# Schema
type Mutation {
login(email: String!, password: String!): LoginResult!
}
union LoginResult = LoginSuccess | InvalidCredentials | AccountLocked
type LoginSuccess {
user: User!
token: String!
}
type InvalidCredentials {
message: String!
}
type AccountLocked {
message: String!
unlockAt: DateTime
}
# Resolver
const resolvers = {
Mutation: {
login: async (_, { email, password }, { db }) => {
const user = await db.user.findByEmail(email);
if (!user || !await verifyPassword(password, user.hash)) {
return {
__typename: 'InvalidCredentials',
message: 'Invalid email or password'
};
}
if (user.lockedUntil && user.lockedUntil > new Date()) {
return {
__typename: 'AccountLocked',
message: 'Account temporarily locked',
unlockAt: user.lockedUntil
};
}
return {
__typename: 'LoginSuccess',
user,
token: generateToken(user)
};
}
},
LoginResult: {
__resolveType(obj) {
return obj.__typename;
}
}
};
# Client query
const LOGIN = gql`
mutation Login($email: String!, $password: String!) {
login(email: $email, password: $password) {
... on LoginSuccess {
user { id name }
token
}
... on InvalidCredentials {
message
}
... on AccountLocked {
message
unlockAt
}
}
}
`;
// Handle all cases
const result = data.login;
switch (result.__typename) {
case 'LoginSuccess':
setToken(result.token);
redirect('/dashboard');
break;
case 'InvalidCredentials':
setError(result.message);
break;
case 'AccountLocked':
setError(`${result.message}. Try again at ${result.unlockAt}`);
break;
}
## Sharp Edges
### Each resolver makes separate database queries
Severity: CRITICAL
Situation: You write resolvers that fetch data individually. A query for
10 posts with authors makes 11 database queries. For 100 posts,
that's 101 queries. Response time becomes seconds.
Symptoms:
- Slow API responses
- Many similar database queries in logs
- Performance degrades with list size
Why this breaks:
GraphQL resolvers run independently. Without batching, the author
resolver runs separately for each post. The database gets hammered
with repeated similar queries.
Recommended fix:
# USE DATALOADER
import DataLoader from 'dataloader';
// Create loader per request
const userLoader = new DataLoader(async (ids) => {
const users = await db.user.findMany({
where: { id: { in: ids } }
});
// IMPORTANT: Return in same order as input ids
const userMap = new Map(users.map(u => [u.id, u]));
return ids.map(id => userMap.get(id));
});
// Use in resolver
const resolvers = {
Post: {
author: (post, _, { loaders }) =>
loaders.userLoader.load(post.authorId)
}
};
# Key points:
# 1. Create new loaders per request (for caching scope)
# 2. Return results in same order as input IDs
# 3. Handle missing items (return null, not skip)
### Deeply nested queries can DoS your server
Severity: CRITICAL
Situation: Your schema has circular relationships (user.posts.author.posts...).
A client sends a query 20 levels deep. Your server tries to resolve
it and either times out or crashes.
Symptoms:
- Server timeouts on certain queries
- Memory exhaustion
- Slow response for nested queries
Why this breaks:
GraphQL allows clients to request any valid query shape. Without
limits, a malicious or buggy client can craft queries that require
exponential work. Even legitimate queries can accidentally be too deep.
Recommended fix:
# LIMIT QUERY DEPTH AND COMPLEXITY
import depthLimit from 'graphql-depth-limit';
import { createComplexityLimitRule } from 'graphql-validation-complexity';
const server = new ApolloServer({
typeDefs,
resolvers,
validationRules: [
// Limit nesting depth
depthLimit(10),
// Limit query complexity
createComplexityLimitRule(1000, {
scalarCost: 1,
objectCost: 2,
listFactor: 10
})
]
});
# Also consider:
# - Query timeout limits
# - Rate limiting per client
# - Persisted queries (only allow pre-registered queries)
### Introspection enabled in production exposes your schema
Severity: HIGH
Situation: You deploy to production with introspection enabled. Anyone can
query your schema, discover all types, mutations, and field names.
Attackers know exactly what to target.
Symptoms:
- Schema visible via introspection query
- GraphQL Playground accessible in production
- Full type information exposed
Why this breaks:
Introspection is essential for development and tooling, but in
production it's a roadmap for attackers. They can find admin
mutations, internal fields, and deprecated but still working APIs.
Recommended fix:
# DISABLE INTROSPECTION IN PRODUCTION
const server = new ApolloServer({
typeDefs,
resolvers,
introspection: process.env.NODE_ENV !== 'production',
plugins: [
process.env.NODE_ENV === 'production'
? ApolloServerPluginLandingPageDisabled()
: ApolloServerPluginLandingPageLocalDefault()
]
});
# Better: Use persisted queries
# Only allow pre-registered queries in production
const server = new ApolloServer({
typeDefs,
resolvers,
persistedQueries: {
cache: new InMemoryLRUCache()
}
});
### Authorization only in schema directives, not resolvers
Severity: HIGH
Situation: You rely entirely on @auth directives for authorization. Someone
finds a way around the directive, or complex business rules don't
fit in a simple directive. Authorization fails.
Symptoms:
- Unauthorized access to data
- Business rules not enforced
- Directive-only security bypassed
Why this breaks:
Directives are good for simple checks but can't handle complex
business logic. "User can edit their own posts, or any post in
groups they moderate" doesn't fit in a directive.
Recommended fix:
# AUTHORIZE IN RESOLVERS
// Simple check in resolver
Mutation: {
deletePost: async (_, { id }, { user, db }) => {
if (!user) {
throw new AuthenticationError('Must be logged in');
}
const post = await db.post.findUnique({ where: { id } });
if (!post) {
throw new NotFoundError('Post not found');
}
// Business logic authorization
const canDelete =
post.authorId === user.id ||
user.role === 'ADMIN' ||
await userModeratesGroup(user.id, post.groupId);
if (!canDelete) {
throw new ForbiddenError('Cannot delete this post');
}
return db.post.delete({ where: { id } });
}
}
// Helper for field-level authorization
User: {
email: (user, _, { currentUser }) => {
// Only show email to self or admin
if (currentUser?.id === user.id || currentUser?.role === 'ADMIN') {
return user.email;
}
return null;
}
}
### Authorization on queries but not on fields
Severity: HIGH
Situation: You check if a user can access a resource, but not individual
fields. User A can see User B's public profile, and accidentally
also sees their private email and phone number.
Symptoms:
- Sensitive data exposed
- Privacy violations
- Field data visible to wrong users
Why this breaks:
Field resolvers run after the parent is returned. If the parent
query returns a user, all fields are resolved - including sensitive
ones. Each sensitive field needs its own auth check.
Recommended fix:
# FIELD-LEVEL AUTHORIZATION
const resolvers = {
User: {
// Public fields - no check needed
id: (user) => user.id,
name: (user) => user.name,
// Private fields - check access
email: (user, _, { currentUser }) => {
if (!currentUser) return null;
if (currentUser.id === user.id) return user.email;
if (currentUser.role === 'ADMIN') return user.email;
return null;
},
phoneNumber: (user, _, { currentUser }) => {
if (currentUser?.id !== user.id) return null;
return user.phoneNumber;
},
// Or throw instead of returning null
privateData: (user, _, { currentUser }) => {
if (currentUser?.id !== user.id) {
throw new ForbiddenError('Not authorized');
}
return user.privateData;
}
}
};
### Non-null field failure nullifies entire parent
Severity: MEDIUM
Situation: You make fields non-null for convenience. A resolver throws or
returns null. The error propagates up, nullifying parent objects,
until the whole query response is null or errors out.
Symptoms:
- Queries return null unexpectedly
- One error affects unrelated fields
- Partial data can't be returned
Why this breaks:
GraphQL's null propagation means if a non-null field can't resolve,
its parent becomes null. If that parent is also non-null, it
propagates further. One failing field can break an entire response.
Recommended fix:
# DESIGN NULLABILITY INTENTIONALLY
# WRONG: Everything non-null
type User {
id: ID!
name: String!
email: String!
avatar: String! # What if no avatar?
lastLogin: DateTime! # What if never logged in?
}
# RIGHT: Nullable where appropriate
type User {
id: ID! # Always exists
name: String! # Required field
email: String! # Required field
avatar: String # Optional - may not exist
lastLogin: DateTime # Nullable - may be null
}
# For lists:
# [User!]! - Non-null list of non-null users (recommended)
# [User!] - Nullable list of non-null users
# [User]! - Non-null list of nullable users (rarely useful)
# [User] - Nullable list of nullable users (avoid)
# Rule of thumb:
# - Non-null if always present and failure should fail query
# - Nullable if optional or failure shouldn't break response
### Expensive queries treated same as cheap ones
Severity: MEDIUM
Situation: Every query is processed the same. A simple user(id) query uses
the same resources as users(first: 1000) { posts { comments } }.
Expensive queries starve out cheap ones.
Symptoms:
- Expensive queries slow everything
- No way to prioritize queries
- Rate limiting is ineffective
Why this breaks:
Not all GraphQL operations are equal. Fetching 1000 users with
nested data is orders of magnitude more expensive than fetching
one user. Without cost analysis, you can't rate limit properly.
Recommended fix:
# QUERY COST ANALYSIS
import { createComplexityLimitRule } from 'graphql-validation-complexity';
// Define complexity per field
const complexityRules = createComplexityLimitRule(1000, {
scalarCost: 1,
objectCost: 10,
listFactor: 10,
// Custom field costs
fieldCost: {
'Query.searchUsers': 100,
'Query.analytics': 500,
'User.posts': ({ args }) => args.limit || 10
}
});
// For rate limiting by cost
const costPlugin = {
requestDidStart() {
return {
didResolveOperation({ request, document }) {
const cost = calculateQueryCost(document);
if (cost > 1000) {
throw new Error(`Query too expensive: ${cost}`);
}
// Track cost for rate limiting
rateLimiter.consume(request.userId, cost);
}
};
}
};
### Subscriptions not properly cleaned up
Severity: MEDIUM
Situation: Clients subscribe but don't unsubscribe cleanly. Network issues
leave orphaned subscriptions. Server memory grows as dead
subscriptions accumulate.
Symptoms:
- Memory usage grows over time
- Dead connections accumulate
- Server slows down
Why this breaks:
Each subscription holds server resources. Without proper cleanup
on disconnect, resources accumulate. Long-running servers
eventually run out of memory.
Recommended fix:
# PROPER SUBSCRIPTION CLEANUP
import { PubSub, withFilter } from 'graphql-subscriptions';
import { WebSocketServer } from 'ws';
import { useServer } from 'graphql-ws/lib/use/ws';
const pubsub = new PubSub();
// Track active subscriptions
const activeSubscriptions = new Map();
const wsServer = new WebSocketServer({
server: httpServer,
path: '/graphql'
});
useServer({
schema,
context: (ctx) => ({
pubsub,
userId: ctx.connectionParams?.userId
}),
onConnect: (ctx) => {
console.log('Client connected');
},
onDisconnect: (ctx) => {
// Clean up resources for this connection
const userId = ctx.connectionParams?.userId;
activeSubscriptions.delete(userId);
}
}, wsServer);
// Subscription resolver with cleanup
Subscription: {
messageReceived: {
subscribe: withFilter(
(_, { roomId }, { pubsub, userId }) => {
// Track subscription
activeSubscriptions.set(userId, roomId);
return pubsub.asyncIterator(`ROOM_${roomId}`);
},
(payload, { roomId }) => {
return payload.roomId === roomId;
}
)
}
}
## Validation Checks
### Introspection enabled in production
Severity: WARNING
Message: Introspection should be disabled in production
Fix action: Set introspection: process.env.NODE_ENV !== 'production'
### Direct database query in resolver
Severity: WARNING
Message: Consider using DataLoader to batch and cache queries
Fix action: Create DataLoader and use .load() instead of direct query
### No query depth limiting
Severity: WARNING
Message: Consider adding depth limiting to prevent DoS
Fix action: Add validationRules: [depthLimit(10)]
### Resolver without try-catch
Severity: INFO
Message: Consider wrapping resolver logic in try-catch
Fix action: Add error handling to provide better error messages
### JSON or Any type in schema
Severity: INFO
Message: Avoid JSON/Any types - they bypass GraphQL's type safety
Fix action: Define proper input/output types
### Mutation returns bare type instead of payload
Severity: INFO
Message: Consider using payload types for mutations (includes errors)
Fix action: Create CreateUserPayload type with user and errors fields
### List field without pagination arguments
Severity: INFO
Message: List fields should have pagination (limit, first, after)
Fix action: Add arguments: field(limit: Int, offset: Int): [Type!]!
### Query hook without error handling
Severity: INFO
Message: Handle query errors in UI
Fix action: Destructure and handle error: const { error } = useQuery(...)
### Using refetch instead of cache update
Severity: INFO
Message: Consider cache update instead of refetch for better UX
Fix action: Use update function to modify cache directly
## Collaboration
### Delegation Triggers
- user needs database optimization -> postgres-wizard (Optimize queries for GraphQL resolvers)
- user needs authentication system -> authentication-oauth (Auth for GraphQL context)
- user needs caching layer -> caching-strategies (Response caching, DataLoader caching)
- user needs real-time infrastructure -> backend (WebSocket setup for subscriptions)
## Related Skills
Works well with: `backend`, `postgres-wizard`, `nextjs-app-router`, `react-patterns`
## When to Use
- User mentions or implies: graphql
- User mentions or implies: graphql schema
- User mentions or implies: graphql resolver
- User mentions or implies: apollo server
- User mentions or implies: apollo client
- User mentions or implies: graphql federation
- User mentions or implies: dataloader
- User mentions or implies: graphql codegen
- User mentions or implies: graphql query
- User mentions or implies: graphql mutationRelated Skills
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