graphql-schema_skill

Overview

This skill guides designers and teams through practical, industry-proven GraphQL schema patterns to build intuitive, secure, and evolvable APIs. It focuses on client-driven design, clear naming and nullability, sensible type modeling, and evolution strategies like deprecation. Use it to make schemas predictable, maintainable, and easier to consume.

How this skill works

The skill inspects schema design decisions and recommends concrete patterns: domain-focused types, interface and union usage, input vs output separation, nullability rules, pagination, and error modeling. It highlights security and ID strategies, enforces list and non-null conventions, and suggests mutation and field patterns to avoid common anti-patterns. The guidance is practical and aimed at preventing breaking changes while improving client ergonomics.

When to use it

• Designing a new GraphQL API or schema from scratch
• Reviewing or refactoring an existing schema for usability or performance
• Deciding on type shapes, nullability, or when to use interfaces vs unions
• Implementing cursor-based pagination, error/result types, or mutation patterns
• Auditing schema surface for security leaks or exposure of implementation details

Best practices

• Design types around client use cases and domain concepts, not database tables
• Be explicit: name clearly, document descriptions, and make nullability intentional
• Use [Type!]! for lists to prefer empty lists over null and avoid null items
• Model mutations as business operations with a single input object and meaningful return payloads
• Prefer enums for fixed value sets, custom scalars for domain types, and Node/ID patterns for refetchability
• Plan for evolution: deprecate before removal and avoid breaking changes

Example use cases

• Creating a new user and associated resources with a single input mutation that returns success/error types
• Converting deeply nested fields into flatter types and explicit connections to improve client performance
• Adding cursor-based pagination to list fields using Connection and Edge patterns
• Replacing ad-hoc string status fields with enums and custom scalars for validation
• Auditing a schema to remove database internals and enforce non-null contracts where appropriate