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.
It reflects a growing approach: precompute a repository index locally so coding agents stop re-searching and re-reading files to rediscover the same answers.
Codebase intelligence for AI and humans: code health scores, auto-generated docs, git analytics, dead code detection, and architectural decisions via MCP.
Understand your codebase without paying your agent to rediscover it.
Repowise indexes your code, call graph, git history, tests, docs and design decisions once, on your machine. Then you and your coding agent ask it things: what calls this, what breaks if I change it, what is dead, what to fix first, and why it was built this way.
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