#python #ai_coding #claude #claude_code #code_review #graphrag #incremental #knowledge_graph #llm #mcp #python #static_analysis #tree_sitter

code-review-graph is a free, local-first tool that builds a structural map of your code to stop AI assistants from re-reading your entire codebase, saving you significant money and time. By using Tree-sitter to parse your code into a graph and tracking changes incrementally, it identifies the exact "blast radius" of a change so your AI only reads the few files that actually matter. This reduces token usage by an average of 82x (up to 528x in best cases), cutting costs and making AI reviews feasible for massive projects like monorepos.

https://github.com/tirth8205/code-review-graph

#go #agent #agent_skills #code_review #code_review_assistant #harness #repository_level_context

OpenCodeReview is a free AI code review tool that checks your code changes, finds bugs and security issues, and gives clear line-by-line comments. It works with Git diffs, full files, and branches, and you can connect it to your own AI model or use it in CI/CD tools. This helps you review code faster, catch more real problems, and spend less time on false alarms.

https://github.com/alibaba/open-code-review

#rust #ai_tools #code_review #rust #tui

This is tuicr, a terminal code review tool with vim keybindings that lets you read diffs, add comments, and send reviews to GitHub, GitLab, clipboard, or stdout. It works with git, jj, and Mercurial, so you can review changes in one place and save time when checking code or sharing feedback.

https://github.com/agavra/tuicr

#python #ai #ast #claude_code #code_analysis #code_understanding #codebase_search #developer_tools #graph_database #knowledge_graph #llm #mcp #mcp_server #memgraph #monorepo #multi_language #python #rag #retrieval_augmented_generation #semantic_search #tree_sitter

Code-Graph-RAG is an open-source tool that reads a codebase, builds a graph of functions, classes, modules, and links, and lets you ask questions, find code, edit safely, and improve code in plain English. It supports many languages and can run as an MCP server for direct use with AI tools. Benefit: you can understand and change large mixed-language projects faster, with less manual searching and fewer mistakes.

https://github.com/vitali87/code-graph-rag