FileDigest Examples
Download sample digest.md and manifest.json artifacts to see how FileDigest packages documents for AI workflows.
This page shows the output shape FileDigest is designed to produce: a readable Markdown digest for people and LLM context windows, plus a structured manifest for audit, ingestion, and automation.
Sample artifacts
What the sample proves
The public files show the output contract a buyer should inspect before signup: a Markdown digest that can move into AI tools and a manifest that records source files, outcomes, page counts, token estimates, and warnings.
For a real production proof trail, see Real output proof and the AI document processing benchmark. They explain how to validate a real packet by file count, page count, warnings, output tokens, privacy checks, and downstream reuse.
What to inspect
The sample digest.md is intentionally plain Markdown. It keeps source boundaries visible and gives the user a clean artifact that can be pasted into ChatGPT, Claude, AI coding tools, or a prompt packet.
The sample manifest.json is meant for repeatability. It records source file names, file sizes, file outcomes, page counts, token estimates, artifact types, and warnings.
Why examples matter
FileDigest is not trying to be a black-box summarizer. The commercial promise is that document preparation should be inspectable before AI analysis begins.