Free tool: https://grape-root.vercel.app/#install Github: https://discord.gg/rxgVVgCh (For debugging/feedback) Someone asked in my previous post how my setup compares to CodeGraphContext (CGC) . So I ran a small benchmark on mid-sized repo. Same repo Same model ( Claude Sonnet 4.6 ) Same prompts 20 tasks across different complexity levels: symbol lookup endpoint tracing login / order flows dependency analysis architecture reasoning adversarial prompts I scored results using: regex verification LLM judge scoring Results Overall GrapeRoot ended up ~31% (average) went upto 90% cheaper per prompt and solved tasks in fewer turns and quality was similar to high than vanilla Claude code Why the difference CodeGraphContext exposes the code graph through MCP tools . So Claude has to: decide what to query make the tool call read results repeat That loop adds extra turns and token overhead. GrapeRoot does the graph lookup before the model starts and injects relevant files into the Model. So the model starts reasoning immediately. One architectural difference Most tools build a code graph . GrapeRoot builds two graphs : • Code graph : files, symbols, dependencies • Session graph : what the model has already read, edited, and reasoned about That second graph lets the system route context automatically across turns instead of rediscovering the same files repeatedly. Full benchmark All prompts, scoring scripts, and raw data: https://github.com/kunal12203/Codex-CLI-Compact Install https://grape-root.vercel.app/ Works on macOS / Linux / Windows submitted by /u/intellinker
Originally posted by u/intellinker on r/ArtificialInteligence