Open Code Review is an open-source CLI tool that uses LLMs to review code diffs and full files with higher precision than general-purpose AI agents while using 9x fewer tokens. It combines deterministic engineering (file selection, rule matching, positioning) with an agent for dynamic decisions, and has been validated across 200 real pull requests from 50 open-source projects.

• Achieves significantly higher precision and F1 scores than Claude Code with the same underlying model, consuming only ~1/9 of the tokens and completing reviews faster
• Uses hard constraints (precise file selection, smart bundling, fine-grained rule matching, external positioning modules) to eliminate common AI agent failures like incomplete coverage and position drift
• Built on production data from Alibaba's internal use across two years serving tens of thousands of developers and identifying millions of defects

After Andrej Karpathy outlined the idea of “LLM Knowledge Bases” on April 3, 2026, developers built Graphify in under 48 hours. Graphify turns any folder of code, docs, and images into an interlinked markdown wiki you can query without vector databases or complex setup. It persists across sessions, builds backlinks and concept maps, and cuts future query costs.

• Karpathy's April 3, 2026 pitch for "LLM Knowledge Bases" proposed replacing RAG's fetch-at-query-time approach with an LLM-generated, persistent markdown wiki.
• Developers built Graphify from that idea in under 48 hours, and it racked up hundreds of GitHub stars within hours of posting.
• Graphify converts any folder (code, docs, images) into an interlinked markdown wiki—summaries, backlinks, concept maps, index—with one command, no vector database or retrieval pipeline needed.
• Because the wiki is plain markdown that compounds with each update, it's transparent, Git-versionable, and cuts future query costs compared to traditional embedding-based retrieval.