Add core/quality/selection.py: rank_with_targets() returns (ranked,
satisfied) where satisfied = a candidate meets a real target (strict).
load_profile_targets()/rank_for_profile() are the DB-backed wrappers.
search_with_fallback now skips a source that can deliver no target-meeting
quality and escalates to the next (source priority still wins among
satisfying sources; first source's results kept as fallback unless the
profile disables it). Returns RAW tracks — the satisfied check is a coarse
source gate; match-filtering + final ranking stay in the orchestrator so
the correct track is never pruned. Ranking is fail-open: a ranking error
never drops a source's real results.
Tested: rank_with_targets satisfied/fallback matrix + engine escalation,
stop-on-first, raw-not-pruned, fallback on/off. Amazon field test updated
for the corrected format token.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
