graphql-architect

Design federated GraphQL architectures across subgraphs with schema validation.

Updated Nov 16, 2025
One-click install
npx skills add https://github.com/daniel-dihardja/menuyukti --skill graphql-architect-daniel-dihardja
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: graphql-architect
Source: https://github.com/daniel-dihardja/menuyukti/tree/main/.agents/skills/graphql-architect
Command: npx skills add https://github.com/daniel-dihardja/menuyukti --skill graphql-architect-daniel-dihardja

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

GraphQL architectures across multiple subgraphs can become complex to coordinate, leading to inconsistent schemas and costly cross-service data fetching.

Core Features & Use Cases

  • Domain Modeling to map business domains to GraphQL type systems.
  • Schema Design with federation directives to compose subgraphs into a single supergraph.
  • Schema Validation and composition checks to ensure correct @key and inter-subgraph references.
  • Resolvers with DataLoader patterns for efficient batching and caching.
  • Security and performance: add query depth/complexity limits, authorization, and optimization.

Quick Start

Design a federated GraphQL architecture by modeling domains, composing subgraph schemas with federation directives, and implementing resolvers with DataLoader patterns.

Frequently Asked Questions about graphql-architect

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

FAQPage Schema
How do I design a GraphQL schema for a federated architecture?▼

Federated GraphQL architecture models business domains into type systems and composes subgraph schemas using federation directives into a unified supergraph. It requires schema-first discipline, proper @key directives, and composition validation.

What is the best way to handle data fetching across multiple GraphQL subgraphs?▼

Implementing resolvers with DataLoader patterns enables efficient batching and caching to prevent costly cross-service data fetching. This standardizes data retrieval across distributed services and reduces redundant queries.

How does DataLoader batching improve GraphQL resolver performance?▼

DataLoader batching improves GraphQL resolver performance by grouping multiple individual requests into a single batch call during a single execution cycle. This minimizes redundant database queries and provides automatic request caching for subsequent resolver operations.

How do I secure a GraphQL API against complex queries?▼

Implement query depth and complexity limits alongside proper authorization directives to secure a GraphQL API against resource-intensive queries. These constraints prevent deeply nested queries from overloading distributed resolver services.

When should I use GraphQL federation instead of a monolithic schema?▼

Use GraphQL federation instead of a monolithic schema when your architecture spans multiple distributed services requiring independent domain modeling and schema composition. Federation enables separate subgraphs to unify into a single supergraph while maintaining schema-first discipline and autonomous deployment.

Do I need schema validation in CI for GraphQL subgraph composition?▼

Schema validation in CI is required to ensure correct @key directives and validate inter-subgraph references during GraphQL composition. Automated CI checks prevent breaking changes and ensure the supergraph composes correctly across distributed services.