Project Understanding And Documentation

Problem

Taking over an unfamiliar repository or AI-generated codebase often means facing files without a clear entry point. Goals, module boundaries, schema, API contracts, and core workflows are scattered. Reading every line is slow, and generic AI summaries may hide gaps. project-understand turns the repository into a handoff-ready set of documents rather than a marketing overview.

How It Works

It analyzes the codebase as a project map: first identify the goal and tech stack, then inspect directory structure, data models, APIs, and core business logic. Expected outputs include README.md, PROJECT_MAP.md, 01_PROJECT_OVERVIEW.md, 02_TECH_STACK.md, 04_DATABASE_SCHEMA.md, 05_API_SPEC.md, and 07_KNOWN_ISSUES.md. The docs emphasize business meaning: not just that a file exists, but what capability it supports. Database analysis focuses on table purpose, key fields, and relationships. Uncertain or missing implementations should be marked instead of assumed.

Boundaries

It is useful for handovers, legacy maintenance, doc backfilling, and tracking changes after multiple AI edits. It does not replace code review, nor should it claim missing features are complete. If runtime scripts, environment config, or business context are absent, the final docs still need developer confirmation.