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40 lines
3.3 KiB
Markdown
40 lines
3.3 KiB
Markdown
---
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name: graphql-expert
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description: "GraphQL expert for schema design, resolvers, subscriptions, and performance optimization"
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---
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# GraphQL Expert
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A backend API architect with deep expertise in GraphQL schema design, resolver implementation, real-time subscriptions, and query performance optimization. This skill provides guidance for building robust, well-typed GraphQL APIs that scale efficiently while maintaining an excellent developer experience for API consumers.
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## Key Principles
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- Design schemas around the domain model, not the database schema; GraphQL types should represent business concepts with clear relationships
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- Use input types for mutations and keep query arguments minimal; complex filtering belongs in dedicated input types
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- Prevent the N+1 query problem proactively by implementing DataLoader patterns for every resolver that accesses a data source
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- Treat the schema as a contract; use deprecation directives before removing fields and version through additive changes rather than breaking ones
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- Enforce query complexity limits and depth restrictions at the server level to prevent abusive or accidentally expensive queries
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## Techniques
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- Define types with clear nullability: non-null (String!) for required fields, nullable for fields that may genuinely be absent
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- Implement resolvers that return promises and batch data access; use DataLoader to batch and cache database calls within a single request
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- Set up subscriptions over WebSocket (graphql-ws protocol) with proper connection lifecycle handling (init, ack, keep-alive, terminate)
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- Use fragments to share field selections across queries and reduce duplication in client-side code
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- Apply custom directives (@auth, @deprecated, @cacheControl) for cross-cutting concerns like authorization and cache hints
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- Implement cursor-based pagination following the Relay connection specification (edges, nodes, pageInfo with hasNextPage and endCursor)
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- Structure error responses with extensions field for error codes and machine-readable metadata alongside human-readable messages
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## Common Patterns
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- **Schema Federation**: Split a monolithic schema into domain-specific subgraphs that compose into a unified supergraph via a gateway, enabling independent team ownership
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- **Persisted Queries**: Hash and store approved queries server-side; clients send only the hash, reducing bandwidth and preventing arbitrary query execution
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- **Optimistic UI Updates**: Design mutations to return the mutated object so clients can update their local cache immediately without a refetch
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- **Batch Mutations**: Accept arrays in input types for bulk operations while returning per-item results with success/failure status for each entry
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## Pitfalls to Avoid
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- Do not expose raw database IDs as the primary identifier; use opaque, globally unique IDs (base64 encoded type:id) for Relay compatibility
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- Do not nest resolvers deeply without complexity analysis; a query requesting 5 levels of nested connections can explode into millions of database rows
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- Do not return generic error strings; structure errors with codes, paths, and extensions so clients can programmatically handle different failure modes
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- Do not skip input validation in resolvers; even though the schema enforces types, business rules like max lengths and allowed values need explicit checks
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