agency-lsp-index-engineer

Orchestrate multiple Language Server Protocol clients into a unified semantic graph.

Updated Jul 23, 2026
One-click install
npx skills add https://github.com/rajyeole6/AI-RECRUITER --skill agency-lsp-index-engineer-rajyeole6
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agency-lsp-index-engineer
Source: https://github.com/rajyeole6/AI-RECRUITER/tree/main/.agents/skills/lsp-index-engineer
Command: npx skills add https://github.com/rajyeole6/AI-RECRUITER --skill agency-lsp-index-engineer-rajyeole6

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires typescript-language-server, intelephense, gopls, rust-analyzer, pyright.

What problem does it solve?

This skill solves the fragmentation of code intelligence by orchestrating multiple Language Server Protocol (LSP) clients to create a unified, searchable semantic graph of a codebase.

Core Features & Use Cases

  • Multi-Language Orchestration: Simultaneously manages LSP clients for TypeScript, PHP, Go, Rust, and Python.
  • Semantic Graph Construction: Transforms LSP responses into a cohesive graph schema representing files, symbols, and their relationships.
  • Real-time Navigation: Enables sub-100ms lookups for definitions, references, and hover documentation across large-scale projects.

Quick Start

Use the agency-lsp-index-engineer skill to initialize the LSP orchestrator and build a semantic graph for the current project directory.

Frequently Asked Questions about agency-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 (LSP) clients to index symbols and relationships into a cohesive graph schema. This approach transforms fragmented LSP responses into a searchable index for cross-language codebase navigation.

What is the best way to index code intelligence for large-scale projects with sub-100ms query performance?▼

Index code intelligence for large-scale projects by constructing a semantic graph with real-time updates and efficient caching. This maintains sub-100ms response times for developer queries, enabling fast lookups for definitions, references, and hover documentation.

Can I use LSP clients for TypeScript, PHP, Go, Rust, and Python simultaneously?▼

Yes, you can manage LSP clients for TypeScript, PHP, Go, Rust, and Python simultaneously. The orchestrator coordinates these language servers to generate a unified, searchable semantic graph representing files and symbols across all supported languages.

How does semantic indexing handle real-time code navigation and references?▼

Semantic indexing handles real-time code navigation by transforming LSP responses into a cohesive graph schema. It enables sub-100ms lookups for definitions, references, and hover documentation by applying real-time graph updates and efficient caching.

Does code intelligence graph construction work with existing language servers like gopls and rust-analyzer?▼

Yes, code intelligence graph construction works with existing language servers like gopls and rust-analyzer. It orchestrates these LSP clients alongside typescript-language-server, intelephense, and pyright to generate a unified semantic graph of codebases.