lsp-index-engineer

Orchestrate LSP clients into a unified semantic graph of code symbols.

Updated Mar 16, 2026

Search Tags:#performance #lsp #code intelligence #polyglot #language server #semantic graph

Ready to run

npx skills add https://github.com/Likas07/t3code-skills --skill lsp-index-engineer-likas07

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: lsp-index-engineer
Source: https://github.com/Likas07/t3code-skills/tree/main/skills/lsp-index-engineer
Command: npx skills add https://github.com/Likas07/t3code-skills --skill lsp-index-engineer-likas07

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses the challenge of fragmented code intelligence across multiple programming languages by orchestrating Language Server Protocol (LSP) clients and building a unified semantic graph.

Core Features & Use Cases

LSP Orchestration: Manages concurrent LSP clients for various languages (TypeScript, PHP, Go, Rust, Python).
Semantic Indexing: Creates a unified graph of code symbols (files, functions, classes) and their relationships.
Performance Optimization: Aims for sub-500ms response times for code intelligence features like go-to-definition and hover.
Use Case: Integrate multiple language servers into a single system that provides real-time code navigation and understanding across a polyglot codebase.

Quick Start

Configure the LSP/Index Engineer to orchestrate TypeScript and PHP language servers for a given project.

Frequently Asked Questions about lsp-index-engineer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I build a unified semantic graph across multiple programming languages?▼

Build a unified semantic graph by orchestrating multiple Language Server Protocol clients to transform LSP responses into a cohesive schema with nodes for files and symbols, plus edges for imports and calls across heterogeneous codebases.

What is the best way to get real-time code intelligence in a polyglot codebase?▼

Real-time code intelligence in a polyglot codebase is achieved by orchestrating concurrent LSP clients for languages like TypeScript, PHP, Go, Rust, and Python to index symbols and relationships into a unified semantic graph.

How does LSP orchestration handle code navigation for large repositories?▼

LSP orchestration handles large repositories by optimizing for sub-500ms response times and scaling to support over 25k symbols, ensuring fast go-to-definition and hover features across the indexed semantic graph.

Can I integrate TypeScript and PHP language servers into a single code intelligence system?▼

Yes, you can integrate TypeScript and PHP language servers into a single system by configuring the LSP orchestration to manage concurrent clients and map their responses into a unified semantic graph schema.

Why does code intelligence become fragmented across heterogeneous programming languages?▼

Code intelligence becomes fragmented because individual language servers operate in isolation, requiring an orchestration layer to transform disparate LSP responses into a cohesive semantic graph of files, symbols, and their relationships.

What are the performance limitations of indexing 25k symbols via LSP?▼

Indexing over 25k symbols via LSP is optimized for sub-500ms response times, though actual performance depends on efficiently orchestrating concurrent clients and transforming their responses into the unified semantic graph.