- header_words.py: modelspec.trigger_phrase, else the tags most training pictures share
(ss_tag_frequency, generic ones left out); the scanner keeps them as
anomalous_header_words when Civitai gives no trigger words, metadata gives headerWords,
model search finds them.
- model_kind: Flux Schnell told from Dev (no guidance_in), Z-Image from Lumina 2 (caption
embedder width, a GGUF by parameter count); RULES 3 so kept header answers are read again.
- api/model_guide.py + model_profiles.json: GET /anomalous/model_guide for the model details
(example settings, header words, the text encoder and VAE a diffusion models file needs,
found by name), and get_model's header_words and usage for the AI.
- model_advice.example_settings gives the author's example settings as values;
author_examples says them in words as before.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
