HarnessKit scans a codebase, filters out noise, and generates AI‑friendly snapshots with architecture maps, domain models, and usage guides. It runs specialized LLM agents, validates their JSON output, and produces ready‑to‑commit documentation for tools like Claude, Cursor, and Copilot. Ideal for consultants and dev teams who need to hand off clean, annotated repos to AI assistants, saving manual effort and reducing errors. Compared to ad‑hoc scripts, it offers a unified, extensible workflow with built‑in validation and deep‑mode sampling.
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