Adopt the realism pass and refresh screenshots/docs

- add the v2 runtime picks: per-phase skyline panoramas, brick, sidewalk
  pavers, dry/wet asphalt, awning canvas, and their normal maps
- add the realism tooling and evidence: tools/scene_concepts.py, capture_realism.gd,
  concept frames, reports/sheets, and tests
- retune phase lighting/fog/exposure, add sun yaw, brighten the night glow,
  add the flashlight beam mesh, and rebuild the planter/tree assets
- regenerate all eleven staged screenshots from the current build; compare is
  11 good / 0 bad
- finish the visual-alignment closeout in DONE/TODO, update architecture,
  blender-assets, PLAN, and ignore rules (editable Blender sources untracked)
- keep the judge retry and document the verified default judge model

Verification: headless 227/227; Python tooling 86/86; check_screenshots 11/11.

PLAN.md

@@ -420,6 +420,42 @@ frame budget measured by `smoke_npc_budget.gd`. See
 [`docs/plan-graphics-v0.6.md`](docs/plan-graphics-v0.6.md) and
 [ADR-0013](docs/adr/0013-blender-authored-npc-characters.md).
 
+### Realism pass
+
+The target look is the realistic 3D-game frames in `docs/screens/designs/` and the larger
+example set in `docs/screens/concepts/`: hazy, layered city depth, believable materials, and
+warm practical lights at night. Readability still comes first. Silhouettes, the focus ring and
+the HUD must stay clear, and the GL Compatibility renderer stays.
+
+- **Backgrounds.** The flat, black-box skyline strip is retired in favour of AI-generated
+  panoramic skylines (Hollywood mid-rises, palms, hills) for day, dusk and night. Each one is a
+  transparent-sky 4:1 strip that tiles horizontally on the existing backdrop ring, and the night
+  variant has lit windows.
+- **Textures.** Higher-detail seamless 1024² tiles with derived normal maps for brick, granite,
+  sidewalk pavers, asphalt (dry and wet), steps, awning canvas and stucco, at the current UV
+  scales.
+- **Process.** `tools/scene_concepts.py` generates (never overwriting existing images),
+  processes, audits and judges. `src/test/capture_realism.gd` captures the same camera shots
+  with the current and the candidate assets, swapped at runtime, so a candidate is compared
+  before any game code changes. Candidates are adopted only when the realism report (Pillow
+  detail metrics + vision-model realism scores) improves and `screen_designs.py judge` shows no
+  new `diff`.
+- **Storage.** Raw AI output: `assets/textures/ai/v2/raw/` (local, gitignored). Game-ready
+  candidates: `assets/textures/ai/game_ready/v2/`. Scene references: `docs/screens/concepts/`.
+  Trial captures and reports: `docs/screens/realism/<run>/`.
+- **First result (2026-11-01).** Swapping in the v2 skyline and tiles raised the judge's mean
+  backdrop score from 2.6 to 4.0 and texture detail from 1.2 to ~1.7. Overall realism stayed at
+  ~2/10; the limits were lighting and exposure, flat facades and blob foliage, not textures.
+- **Adopted (2026-11-01).** The v2 picks are now the runtime skyline and surface set, the phase
+  lighting was retuned (exposure, darker dusk/late, practical lights, wet asphalt at night), the
+  backdrop is a fog-free 90 m panorama ring per phase, the facade gained plinth/string
+  courses/cornice/pilasters/glazing bars, and the library trees and shrubs are denser. Judge
+  scores on the like-for-like shots rose on every sub-score (overall 0.8 → 1.0, backdrop
+  0.6 → 1.6) with the metric gap down 0.444 → 0.348
+  (`docs/screens/realism/2026-11-01-adopt/`). The remaining gap to the concepts is the low-poly
+  character and prop fidelity, a visible flashlight beam at night, and the entrance still being
+  ~20 % brighter than the concept (`TODO.md` → Realism follow-ups).
+
 The scenario should test the player’s ability to distinguish ordinary Hollywood Boulevard activity from a genuine security problem. The best solution is usually a simple gesture, clear direction, or credential check rather than immediate escalation.
 
 Future venues can reuse this structure while changing the rules, equipment, staff roles, and types of access decisions.