- 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>
The prompt_pose skill now comes in the form for the model the canvas's sampler uses:
its drawing model's parameters are counted from the file's header (model_kind.
diffusion_params: safetensors shapes, GGUF tensor dims; a checkpoint's text encoders
and VAE left out), so a compressed GGUF counts like the full model. From 10 billion
(Flux.1, Flux.2, Qwen-Image) the AI is told hands and hard poses come out well and
not to hide or simplify; under it, the clear-pose and optional hand-hiding advice;
when the model cannot be told, both cases.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
- An AI app calling by an older tool list (tool_help or use_tool not offered,
use_tool for a tool offered directly, a tool the list lacks) is told so, and
the task header shows how to reconnect until the app fetches tools/list again.
- add_lora / set_model compare the base models on the model line
(model_advice.py; the page reports the line) and add base_model_note.
- get_model gives author_examples (sampler, steps, CFG, size, a LoRA's weight
from the Civitai record's example pictures) and the version name.
- run_workflow says ComfyUI's refusal as which node, what is wrong and the tool
that fixes it (run_refusal.py; mcp_run.js passes the refusal as data).
- Gates "When I don't answer": wait for me, or go with the recommendation once
the waiting time runs out (choices with a recommended option only), handed to
the AI in the same call and shown on the stage and under Decisions.
- A tool budget test (count, size, description length, required arguments) and
the exam tasks with their scorecard (docs/architecture/tool-exam.md,
tools/tool_exam.mjs). The tool set's text recommends Full for Antigravity.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>