CodeScene

Headlines · 2

1. Oct 12
   Agent refactors 300K lines of C in three weeks, Code Health 5.6 to 10.0

   CodeScene published a case study in which a coding agent refactored a 300,000-line C codebase in three weeks for about $4,000 in tokens, making 2,903 commits across 726 files, changing 252,055 lines and raising the repo's Code Health score from 5.6 to 10.0. The code is an open-source decompilation project for Street Fighter III: 3rd Strike; the agent used the CodeHealth MCP Server's deterministic score and a replay-trajectory harness comparing state hashes frame by frame, and built a playbook of 22 transformations and 82 notes. CodeScene founder Adam Tornhill called it the first large-scale superhuman AI performance he had seen; the team mostly used Claude Opus with Claude Code, saying it beat Codex with Sol at spotting emerging patterns. Commenters split over what it proves: supporters said frame-by-frame replay is a higher bar than passing tests, while critics asked about scope, merges, unmeasured performance and model-tuned harness bias. A follow-up study with Lund University will have students add features to both the 5.6 and 10.0 versions; projections of ~70% fewer AI defects and ~45% less token waste came from earlier research.

   InfoQ 中文 AI&大模型 · 🔥 0
2. Oct 12
   Repowise: open-source codebase index for AI coding agents

   Repowise is an open-source (AGPL-3.0, with a commercial license option) codebase intelligence tool that builds a local index of the call graph, git history, tests, docs and design decisions for MCP-capable coding agents such as Claude Code, Codex and Cursor. The project claims that on a paired agent loop over 43 questions on django/django it cut the agent's own output by 31.6% (p<0.0001) and reached answers in 3.8 tool calls instead of 7.2, and that on 42 sealed retrieval tasks it found 0.876 of the files a fix needed versus 0.610 for the next tool. It also claims call-graph precision of 0.976 to 0.995 against the compiler on Go and TypeScript, and says graph, health and dead-code features make zero LLM calls and need no API key.

   GitHub Trending · Python · 🔥 0

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