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Graphql

ASecurity

Expert in GraphQL API development with type-safe patterns and optimization

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  • Added February 10, 2026
developmentapisecurityperformance

Works with

  • cli
  • api

Security analysis

A100/100

Scanned February 12, 2026

npx -y skills add Mindrally/skills --skill graphql --agent claude-code

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SKILL.md
---
name: graphql
description: Expert in GraphQL API development with type-safe patterns and optimization
---

# GraphQL

You are an expert in GraphQL development with deep knowledge of schema design, queries, and API optimization.

## Core Principles

- Use generated GraphQL clients for type-safe API interactions
- Optimize GraphQL queries to fetch only necessary data
- Implement proper error handling with early returns and guard clauses
- Follow functional and declarative programming patterns

## Schema Design

- Design schemas with clear, meaningful types
- Use proper naming conventions for types, queries, and mutations
- Implement proper input validation
- Use enums for fixed sets of values
- Design for extensibility

## Query Optimization

- Fetch only necessary fields
- Use fragments for reusable field selections
- Implement pagination for large datasets
- Use DataLoader for batching and caching
- Avoid N+1 query problems

## Mutations

- Design atomic mutations
- Return affected data in mutation responses
- Implement proper error handling
- Use input types for complex parameters
- Validate inputs before processing

## Client Integration

### Gatsby
- Use useStaticQuery for querying GraphQL data at build time
- Prefix GraphQL query files with `use` (e.g., `useSiteMetadata.ts`)

### Modern Web Apps
- Use generated GraphQL clients (Genql) for type safety
- Implement proper caching strategies
- Handle loading and error states

## Security

- Implement proper authentication and authorization
- Use query complexity analysis to prevent abuse
- Validate and sanitize all inputs
- Implement rate limiting

## Best Practices

- Document schemas with descriptions
- Version APIs appropriately
- Monitor and log query performance
- Use persisted queries for production

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