Schema Changes Shouldn't Break Your Clients - Building a Validation Layer
A service that ensures the safety of 2,500+ GraphQL operations against schema changes across a supergraph - catching breaking changes before production release
Found 4 projects
A service that ensures the safety of 2,500+ GraphQL operations against schema changes across a supergraph - catching breaking changes before production release
A personal tool for turning rough prompt intent into production-ready LLM prompts through a 4-layer processing pipeline — expanding intent, selecting reasoning strategy, enforcing output schema, and optimizing for the target model.
An AI-driven workflow system that automates multi-stage schema review at eBay — replacing repeated manual context-gathering with structured, stateful Claude workflows that carry context across async review stages.
A context retrieval system that ingests and indexes schema from a centralized schema store, surfacing historical evolution data to support debugging and reduce time spent identifying breaking changes across distributed services.