LSP/Index Engineer

Build a unified semantic graph by orchestrating multiple LSP clients across languages like TypeScript, PHP, Go, Rust, and Python to collect files, extract symbols, and resolve references into a cohesive structure.

Real-time semantic indexing handles incremental code updates by applying caching and scalable graph storage, ensuring go-to-definition and hover responses remain sub-100ms after changes in multi-language codebases.

Yes, LSP orchestration unifies code intelligence across TypeScript and PHP by collecting files and resolving references from diverse language servers into a single graph for accurate navigation.

The best way to import and export LSIF data for offline querying is using LSIF import/export capabilities alongside a SQLite/JSON cache, enabling fast startup and offline semantic graph queries.

Semantic graph construction supports cross-language reference resolution by creating nodes for files and symbols with edges for contains, imports, calls, and references, ensuring consistent navigation across diverse language servers.

Limitations of building a unified semantic graph with language servers include fragmented ecosystems yielding disjointed code intelligence, requiring strict LSP protocol compliance and complex orchestration to maintain consistent cross-language navigation.