Stunspot's Guide to Gastronomic Engineering — A practical canon for gastronomic engineering knowledge, reasoning, and AI/RAG use.

Stunspot’s Guide to Gastronomic Engineering

A practical canon for gastronomic engineering knowledge, reasoning, and AI/RAG use.

This site is the navigation layer for a model-facing knowledge canon about food as engineered matter. The corpus itself lives in the repository under knowledge-packs/, not inside docs/.

The canon is designed to help AI/RAG systems reason about culinary formulation with stable terminology and source-traceable structure: phase states, control variables, thermodynamic and biochemical pathways, constraint compilers, dietary operating modes, substitution graphs, and failure diagnosis.

It is human-readable, but its primary purpose is machine ingestion. Treat the pages here as orientation; treat the files under knowledge-packs/ as the operational corpus.



Directory Policy

Area Purpose
docs/ Navigation, GitHub Pages metadata, and usage guidance.
knowledge-packs/by-report/ Canonical individual source reports.
knowledge-packs/compiled-packs/ Grouped upload packs for most AI/RAG workflows.
knowledge-packs/omnibus/ Whole-corpus bundle for single-file import or archive.

There is no docs/reports/ directory. The individual reports live only in knowledge-packs/by-report/.


Corpus Shape

The recommended default for most AI/RAG workflows is the compiled-pack set.


Operational Frame

This canon is best used when the model needs to answer questions like:

This is formulation knowledge, not medical or allergen-safety authority. Validate clinical, labeling, and safety decisions against qualified sources.