feat: add witnessed knowledge and wind ambience
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@@ -667,14 +667,34 @@ Completed:
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logs. Waterfall mist is anchored to the waterfall instead of the village
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origin, duplicate wind layers are separated, and Metal smoke/wind
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materials retain restrained transparency.
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17. Coherent breeze pass: overlapping valley-wide white stroke/speck emitters
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were removed. Tree canopies now bend gently in one prevailing direction
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with stable per-tree phase and slow gust variation, while chimney smoke
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leans with the same breeze. Day/night lighting now follows the simulation
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clock even when the world initializes first, with the sunrise/sunset tints
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applied in the correct order. The gameplay camera remains unchanged.
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18. Stylized player readability: the remaining gray player capsule is replaced
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by a compact multi-part figure with a warm scarf/satchel accent and
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velocity-driven walk motion. Collision, controls, and the elevated
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staggered follow camera remain unchanged.
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19. Event-caused trust consequence: hungry familiar NPCs can gain directed
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trust from a real food-deposit event, retain that event as the inspectable
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cause, and redirect ordinary work to help a starving acquaintance. The
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state is versioned and deterministic rather than presentation-only flavor.
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20. Calligraphic gust ambience: one terrain-aware controller now emits only
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two or three tapered sage/amber/aqua ribbons at a time, with long quiet
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intervals and a shared canopy/smoke direction. The shader draws each line
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head-to-tail like a soft brush mark; repeated bursts cannot stack into the
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old scratch/gnat field.
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21. Witnessed event knowledge: objective food-deposit events create separate
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known-event references for their actor and nearby living NPCs. Knowledge
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gates trust, produces a real informed-versus-uninformed choice divergence,
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survives schema-v5 save/load, and appears in the NPC inspector.
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Next:
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1. Replace the remaining player capsule with a matching stylized presentation,
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while preserving the elevated top-down follow, gentle dead-zone lag, and
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cozy farm-builder readability.
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2. Continue with the relationship consequence work in `LEARNING_ROADMAP.md`
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before expanding visual scope further.
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1. Add one provenance-aware NPC-to-NPC fact transfer, then bounded
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importance/retention rules, as sequenced in `LEARNING_ROADMAP.md`.
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Do not start with GIS data, a full city, a large asset pack, or more NPC
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mechanics. The next proof is a beautiful stage for the systems that already
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