LSP/Index Engineer

Build a unified semantic graph by orchestrating multiple LSP 3.17 clients and transforming their responses into a consistent nodes-and-typed-edges model. This process merges definition, reference, and hover data across TypeScript, PHP, Go, Rust, and Python into one graph.

Stream incremental code intelligence updates by applying graph diffs over WebSocket with strict performance contracts. This approach ensures atomic consistency while maintaining sub-100ms latency for real-time semantic visualization and navigation services.

LSP capability negotiation for polyglot code intelligence involves concurrently initializing and querying multiple language servers without assuming supported features. It enforces strict capability checks before transforming responses into a unified semantic graph.

Yes, you can use a single semantic graph for navigation and hover services across different programming languages. It generates a symbol navigation index with strict performance contracts for /graph and /nav/:symId lookups, enforcing definition and reference correctness.

Achieve sub-100ms latency for semantic code navigation by generating a symbol navigation index and streaming graph diffs over WebSocket. This requires incremental graph updates with atomic consistency and strict performance contracts for /nav/:symId lookups.

A polyglot LSP aggregator returns inconsistent data when it lacks integrity guarantees in the semantic graph. You must enforce definition and reference correctness while transforming diverse LSP responses into a consistent nodes-and-typed-edges model.