RepoMap gives AI coding agents architectural maps without sending source code

RepoMap addresses a concrete inefficiency in how modern coding agents work. Currently, agents spend significant effort reconstructing project architecture by opening files, following imports, and inspecting folder structures—a repetitive task that consumes thousands of tokens per session despite being largely deterministic. The tool solves this by separating repository structure extraction from architectural reasoning: a dedicated analyzer identifies imports, module relationships, and definitions without invoking an LLM, producing a compact structural representation that captures the repository's layout. The LLM then operates on this pre-computed model in a single reasoning step, dramatically reducing token usage while enabling richer architectural representations.

The design reflects a practical insight: finding imports, discovering modules, and extracting definitions are deterministic operations that do not require language model intelligence. By offloading this work to a conventional software scanner, RepoMap frees the LLM's context window for actual architectural reasoning—assigning roles, identifying patterns, improving labels, and generating visualization layouts. The tool also preserves source code privacy by ensuring that no actual code is sent to the LLM, only structural metadata. Its integration with AI agents like Claude and OpenCode, plus its interactive visualization for human exploration and Git-aware branch browsing, positions it as infrastructure for both immediate agent efficiency and future architectural diff capabilities.