feat: clothing lane, character sources, and DCC bridges

Bulk import of the working lanes that were living untracked on the PC.

Content:
- characters/  Lena/male body lanes, bakes, texture work, run logs
- clothing/    garment pipeline, configs, gates, contract docs
- garments/    MD-authored garment sources (.zprj/.zpac)
- UAL-Lib/     Universal Animation Library 2 source (.blend/.fbx/.glb)
- tools/       blender_bridge, iclone_bridge, md_bridge, tailor, glm_agent
- docs/, plans/, dev/, .agents/plans/

Repo hygiene:
- .gitattributes: LFS now covers .blend, .zprj, .zpac, .obj, .npy and the
  Reallusion .iAvatar/.ccAvatar/.ccRestore containers. Without this the
  ~3.8 GB in this commit would land as raw blobs. .png/.jpg are left out
  on purpose — ~250 are already tracked raw and converting them would
  rewrite every one without shrinking history.
- .gitignore: exclude /accurig/ (~1 GB AccuRig program files, redistributable
  from Reallusion, nothing authored here) and /dev/null/ (git-lfs hook copies
  dropped by a `>/dev/null` redirect on Windows).

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

characters/female/lena_nude/hires_claude/locate_artifact.py

@@ -0,0 +1,36 @@
+import bpy, sys
+import numpy as np
+W = r"C:\Users\Jeremy\tinqs\animation\characters\female\lena_nude\hires_claude"
+bpy.ops.wm.open_mainfile(filepath=W + r"\03_sculpted.blend")
+ob = max([o for o in bpy.data.objects if o.type=='MESH'], key=lambda o: len(o.data.vertices))
+me = ob.data
+n_v = len(me.vertices)
+co = np.empty(n_v*3); me.vertices.foreach_get("co", co); co = co.reshape(-1,3)
+# face normals -> vertex normal variance (crease detector)
+n_f = len(me.polygons)
+fn = np.empty(n_f*3); me.polygons.foreach_get("normal", fn); fn = fn.reshape(-1,3)
+lt = np.empty(n_f, dtype=np.int32); me.polygons.foreach_get("loop_total", lt)
+ls = np.empty(n_f, dtype=np.int32); me.polygons.foreach_get("loop_start", ls)
+lv = np.empty(len(me.loops), dtype=np.int32); me.loops.foreach_get("vertex_index", lv)
+acc = np.zeros((n_v,3)); acc2 = np.zeros(n_v); cnt = np.zeros(n_v)
+for fi in range(n_f):
+    for k in range(ls[fi], ls[fi]+lt[fi]):
+        vi = lv[k]
+        acc[vi] += fn[fi]; cnt[vi] += 1
+mean = acc / np.maximum(cnt,1)[:,None]
+ml = np.linalg.norm(mean, axis=1)          # 1 = all normals aligned; low = crease/facet
+window = (co[:,1] < 0) & (co[:,2] > 0.58) & (co[:,2] < 0.82) & (np.abs(co[:,0]) < 0.12)
+bad = window & (ml < 0.90) & (cnt > 0)
+print(f"creased verts in front-chest window: {bad.sum()}")
+if bad.sum():
+    b = co[bad]
+    print(f"bbox: x [{b[:,0].min():+.3f},{b[:,0].max():+.3f}]  "
+          f"y [{b[:,1].min():+.3f},{b[:,1].max():+.3f}]  "
+          f"z [{b[:,2].min():+.3f},{b[:,2].max():+.3f}]")
+    # cluster by z-decile to see structure
+    for zlo in np.arange(0.58, 0.82, 0.02):
+        m = bad & (co[:,2] >= zlo) & (co[:,2] < zlo+0.02)
+        if m.sum() > 30:
+            print(f"  z {zlo:.2f}-{zlo+0.02:.2f}: n={m.sum():5d}  "
+                  f"x[{co[m,0].min():+.3f},{co[m,0].max():+.3f}]")
+print("LOCATE_DONE")