Book-YAML 1.0 - An AI-native book format for machine reading

Widespread book formats serve human readers, publishing pipelines, or pretraining scale — none serves machine-learning consumers that must audit their inputs. We present Book-YAML 1.0, a minimal book format for AI reading engines: verbatim text with per-file SHA-256 provenance, stable block identifiers enabling sentence-to-source traceability, explicit prose/verse block typing, curriculum metadata (grade, role, genre), and a language-invariant schema. Every design rule traces to a concrete production failure in the Noemica reading engine: hallucinated LLM extraction (1,135 fabricated facts), silently dropped verse content (8 books read as empty), and encoding corruption (1,431 repaired blocks). Production evidence: 39 books, ≈2.94M words across Hungarian, English, and German — 100% public domain — with 99–100% parse rates and a cross-language invariance measurement (DE↔HU Grimm pairs) that the format made possible.