Mode d’emploi
- Copiez la commande et examinez le paquet avant de l’installer dans votre environnement agent.
- Consultez le document original pour les outils, identifiants et environnements requis.
- Décrivez les entrées et le livrable souhaité ; comparez la sortie aux sources.
npx skills add https://github.com/roble3/cc-blender-skill --skill landmark-fit-repairAvant de commencer
- L’installation n’inclut ni abonnement au modèle, ni quota API, ni accès aux fichiers.
- Étoiles et installations reflètent l’activité, pas un test indépendant de qualité ou de sécurité.
Rendu depuis le dépôt source en conservant titres, exemples, code, tableaux, liens et images.
MCP backend
Use when: Landmark validation, feature-point deltas, control-point repair, face/eye/smile alignment, leaf tip alignment, aura ring fitting, iterative recipe parameter updates.
Before the first Blender call, read ../text-to-blender/references/mcp-backends.md. Prefer official MCP for shared capabilities; preserve the selected backend for the whole task. Tool names in recipes are client/legacy examples: map them through that reference and its agent-host guide.
Landmark Fit Repair
Bbox and IoU are too coarse for final mascot/logo matching. This skill turns named feature drift into recipe edits.
Landmark classes
structural_tip: outer part tips and extrema;shell_corner: face/shell/rim corners;feature: eyes, smile, brows, decals;ring: aura center/radius/dots;depth_marker: side/back/top thickness markers.
Workflow
- Define a landmark JSON for the source reference.
- Detect or render corresponding product landmarks.
- Compare by name and view.
- Convert deltas into repair actions: move boundary control point, scale one component, shift feature curve, tune depth, or adjust aura radius.
- Rebuild from recipe; do not hand-edit final geometry without updating the recipe/manifest.
Hard gates
- No final export when named structural landmarks exceed tolerance.
- Face features must be validated separately from body silhouette.
- Aura/context landmarks must not affect base GLB acceptance.
Script
scripts/landmark_fit_report.pycompares two named-landmark JSON files and emits repair deltas.
Landmark JSON schema
{
"schema": "landmarks.v1",
"image_size": [width, height],
"landmarks": [
{"view":"front", "name":"leaf_top_tip", "class":"structural_tip", "x":627, "y":130}
]
}For part masks, generate initial landmarks from extrema: top/bottom/left/right, centroid, and contour inflection points. Then rename them to semantic names before repair.



