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nimadorostkar
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graphql

Design and optimize GraphQL schemas with DataLoader batching and query cost analysis.

25|3|Updated Jul 14, 2026
Search Tags:#performance#api#schema#graphql#dataloader#federation
One-click install
npx skills add https://github.com/nimadorostkar/Claude-Skills-collection --skill graphql-nimadorostkar
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: graphql
Source: https://github.com/nimadorostkar/Claude-Skills-collection/tree/main/skills/backend/graphql
Command: npx skills add https://github.com/nimadorostkar/Claude-Skills-collection --skill graphql-nimadorostkar

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill addresses the complexities of building and maintaining GraphQL APIs, preventing common pitfalls like N+1 performance issues, insecure endpoints, and poorly designed schemas that mirror databases rather than domain models.

Core Features & Use Cases

  • Schema Design: Guidance on creating intuitive, domain-driven schemas with proper nullability and field naming.
  • Performance Optimization: Implementation of DataLoader batching to eliminate N+1 resolver issues and query cost analysis to prevent resource exhaustion.
  • Security & Reliability: Strategies for depth limiting, persisted queries, and explicit error handling to protect public-facing endpoints.

Quick Start

Use the graphql skill to review my current schema design and suggest improvements for resolver batching and query cost protection.

Frequently Asked Questions about graphql

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I eliminate N+1 query issues in my GraphQL API?▼

To eliminate N+1 query issues in a GraphQL API, implement DataLoader batching within your resolvers to group and cache multiple data fetches into a single request. This prevents cascading database calls during nested data resolution.

What's the best way to secure public GraphQL endpoints from malicious queries?▼

Securing public GraphQL endpoints requires enforcing query complexity analysis, depth limiting, and persisted queries. These strategies prevent resource exhaustion by rejecting excessively deep or expensive queries before execution.

How do I design a GraphQL schema that follows domain models instead of database tables?▼

Designing a domain-driven GraphQL schema involves defining intuitive types, proper nullability, and explicit field naming that reflect business logic rather than mirroring database structures. This ensures resolvers remain decoupled from storage implementation.

Can I use GraphQL federation to scale my backend services?▼

GraphQL federation supports scaling backend services by distributing schema ownership across multiple microservices. This allows complex data fetching across distributed domain boundaries while maintaining a unified API gateway for consumers.

Why does my GraphQL API return poorly structured errors, and how should I model them?▼

Poorly structured GraphQL errors occur when exceptions bubble up unhandled. Explicit error modeling requires defining custom error classes and structured response formats to provide clients with actionable, predictable failure details.

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