Stewie Reflect is a tool that generates an "Owner's Manual" for a software codebase by analyzing a single snapshot of a GitHub repository. Its primary function is to address what the developers call "comprehension debt" – the gap between what a product actually does, what its owner thinks it does, and what can be proven from the code. The output is a structured document that describes what the code does, highlights areas that require attention, and explicitly marks where the evidence ends or where only human judgment can decide. The tool is designed for situations where developers need to modify risky components such as billing, authentication, or usage limits without full understanding of the existing logic. Key features of Stewie Reflect include read-only GitHub integration, where a user can select one repository and branch, and the tool pins the exact commit for analysis. A free preview provides one complete chapter plus all findings for that repository, allowing the user to evaluate the output before purchase. Unlocking the full manual and a Markdown export costs $19 per repository as a one-time fee, with no subscription or recurring charges. The generated manual is organized into chapters that cover aspects such as what happens on specific events, attention items ranked by consequence, and explicit source boundaries that show where the reviewed evidence ends. The tool does not make confident claims when the repository lacks evidence; it labels those items as unknown. Typical use cases include inheriting an unfamiliar codebase, having used AI tools to generate code rapidly, or needing an honest second opinion before investing further in a repository. Users might include non-developer owners who cannot read code, developers who have lost access to the original author, or teams preparing for a major refactor. The workflow starts by connecting GitHub, selecting a repository and branch, then receiving a free repository check. After previewing a sample chapter, the user can decide to unlock the full manual. The sample manual featured in the documentation is based on a real AI bookkeeping application and contains seven chapters with 17 attention items. Technical requirements are minimal on the user side: the repository must be hosted on GitHub, and Stewie Reflect reads the snapshot without executing or modifying the code. The output is delivered as a plain-language document with figures and models, requiring no code reading by the user. The tool is currently in open beta and is built in public. Pricing, privacy details, and FAQ are available on the Stewie Reflect website.