Token-Saving Codebase Explorer

Index first, read less: cut context waste when AI agents explore your codebase.

Problem

When AI explores an unfamiliar codebase, it tends to grep and rg widely, then read files one by one—burning a lot of context before any real work begins. Some developers try Agent LSP tools like serena hoping to index the codebase first for faster symbol lookup, but on large repos the benefit is unclear and there's no way to verify token savings with concrete numbers.

Solution

A local CLI or editor plugin that pre-builds a symbol index before the AI coding assistant starts exploring, then feeds relevant symbols, definitions, and references directly to the AI to reduce blind file reads. It tracks token consumption per task and compares it against a no-index baseline, showing savings clearly. Works with Claude Code, Codex, Cursor, and similar tools.

Users

Developers who frequently use AI coding assistants on large codebases, and individuals or small teams watching API token costs.

MVP

Build a symbol index for a local codebase; provide a pre-explore command that outputs a relevant symbol summary to the AI; log and compare token usage with and without the index; support Claude Code and Codex integration; generate a simple savings report.

Revenue

Free basic tier plus subscription (e.g., $5–15/month) for large-repo indexing and historical stats; team seats as an upgrade.

Why now

Context cost for AI coding assistants is under growing scrutiny; LSP-indexing attempts exist but lack quantified proof of benefit, making a focused token-saving tool viable for a solo developer.