Token-Efficient Living Codebase Docs From PRs And AI Sessions
Almanac keeps a living wiki of a codebase in the repo, updated automatically from pull requests, commits, and AI coding sessions, reaching 129 GitHub stars as teams try to keep docs current in the AI era, but its issues expose the resource discipline such automation demands: a capture sweep wasted around 85 percent of LLM tokens spawning duplicate parallel jobs, an automation agent caused a runaway process cascade of hundreds of CLI processes, and it must detect every coding agent like Codex and OpenCode. Teams want auto-updated docs without runaway cost. The wedge is automated, token-efficient codebase documentation that captures knowledge across every agent safely.
Problem Statement
A team adopts a tool to keep codebase docs current from their AI coding sessions and PRs, but a single capture run wastes most of its LLM tokens on duplicate parallel jobs, an automation agent spirals into hundreds of runaway processes pinning the CPU, and it fails to detect some of the coding agents the team uses. The cost and instability outweigh the benefit, so they go back to stale, manually maintained docs.
The Idea
A living codebase-documentation tool that updates from PRs, commits, and AI sessions across all coding agents, with strict token efficiency and safe automation.
Why Now
AI coding agents generate vast change with little documentation in 2026, and teams want docs that stay current automatically, but Almanac's issues show that naive automation wastes tokens and spawns runaway processes, so token-efficient, safe capture across every agent is the real challenge and the differentiator.
Target User
Engineering teams using AI coding agents who want codebase documentation that stays current automatically
Target Market
Developer documentation and codebase knowledge tooling
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