Extends WIP title-tagging to lower-precision cues (sketch/doodle/scribble) safely.
- wip_title.py: soft matcher (word-anchored; sketchbook/kadoodle don't trip it);
WIP_TITLE_SOFT_SOURCE + soft SQL prefilter; apply_wip_image_tags takes a source arg.
- training_data._AUTO_SOURCES += 'wip_title_soft' → the soft tier is PROVISIONAL and
never trains the wip head (a finished "sketch" can't pollute it). Only the hard
tier (wip_title) + manual train.
- ImportSettings.wip_soft_title_tagging_enabled (OFF by default, opt-in). Migration 0087.
- importer: hard tier wins, soft is the fallback (source wip_title_soft).
- backfill: refactored into a shared _backfill_wip_tier; hard always, soft when enabled.
- heads.soft_wip_conflict_audit + daily beat: score soft-tagged images against content
heads, flag ring-loud ones (PresentationReview mode=process) for the review strip —
the operator's "measure if they got falsely tagged" safety.
- api settings toggle; ImportFiltersForm soft toggle.
- tests: soft matcher pos/neg; soft source not a training positive; audit flags
ring-loud + spares quiet.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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