Exposes a codebase's symbol graph and symbol-aware editing tools to AI agents, enabling targeted symbol lookup, impact analysis, and atomic multi-file edits with reduced context tokens.
Deterministic code intelligence engine — indexes 27 languages into a queryable symbol graph for real-time blast-radius analysis, no embeddings or LLM calls.
Enables LLM agents to efficiently understand and navigate a codebase by providing semantic search over symbols and a reference graph, replacing expensive grep/glob calls with structured tools like definition lookup, caller/callee queries, and change-impact analysis.
Indexes a codebase into a symbol-level graph and exposes tools for finding symbols, querying relationships, and assessing impact, letting AI coding agents answer structural questions in a single call within a token budget.
Token-safe code search for AI agents: queries the language-server index (clangd / Roslyn / tsserver / pyright) instead of grep and returns a token-capped file:line list — ~20x fewer tokens. Symbol-level editing + a grep→index rewrite hook. Local-only, no IDE.
Enables coding agents to perform deterministic, model-free repository analysis and patch operations—tree-sitter repo maps, symbol/reference lookup, and SEARCH/REPLACE parsing/validation—via a CLI or MCP stdio server, without ever calling a language model.