Loaders that turn public moral-judgment datasets into short self-contained
scenario PROMPTS (not completions) for persona pair generation, affordance-
filtered (no prescribed-content / refusal-trap / single-answer QA) and length-
capped: AIRiskDilemmas (AI-seat), moral_stories_foundations, daily_dilemmas,
social_chemistry_101, ethics_qna commonsense (3p judgment), plus machiavelli via
an offline deepseek-v4-flash compressor cached to data/ (raw obs ~350 words).
Moral-RolePlay skipped (fiction/eval-leak). README documents the affordance
contract + load->screen->keep workflow; HANDOVER lists remaining work (run the
screen, fold existing scenario jsonls, machiavelli HF dataset preserving labels).
Also harden validate_persona_axes_openrouter.py: guard resp.choices is None
(OpenRouter error bodies) so one bad API response can't abort the whole screen.
Ported from wassname/w2schar-mini.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
The 52 3p-observer scenarios carry their own question + length
("...what does the actor do next? Answer in one or two sentences."),
but _generation_prompt always appended a 1p "What do you do? Answer in
80-140 words." -- two conflicting questions and a POV flip, so the data
could not reproduce the appendix's 3p measurement through this script
(caught in review).
Add a "self_contained" flag on scenario rows; when set, _generation_prompt
emits the scenario verbatim instead of appending its default 1p question.
Bare-vignette families without the flag are unchanged. README appendix
rewritten to lead with the runnable command and explain the flag.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
wassname