CortexAST

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CortexAST serves as an AI-native code intelligence backend designed to elevate LLM agents' understanding of software projects. By leveraging Tree-sitter and a pure Rust implementation, it transforms raw code into a highly structured, AST-level representation, enabling agents to operate with unparalleled semantic accuracy and token efficiency. This backend allows AI to bypass the noise of traditional human-centric tools, providing a crystal-clear view of codebase architecture, precise symbol analysis, structural refactoring capabilities, and cross-language propagation tracing, ultimately empowering more reliable and impactful AI-driven development.

Características Principales

• JIT Hybrid Vector Search for code relevance and Enterprise Workspace Engine for monorepos.
• 7 GitHub stars
• Nuclear token efficiency for LLM context windows, cutting usage by up to 90%.
• Structural refactoring orchestration with AST-level semantic checkpoints.
• Cross-language blast radius tracing and propagation checklists for shared types.
• AI-native AST codebase mapping and high-fidelity semantic understanding.

Casos de Uso

• Efficiently exploring and understanding codebase architecture for AI agents.
• Performing accurate, structural refactoring operations with semantic diffs and checkpoints.
• Analyzing impact (blast radius) and ensuring cross-language propagation for shared types.