skills/blender-motion-state-inspection/SKILL.md
Use this skill when inspecting Blender characters, rigs, poses, animation retargeting, ground contact, facing direction, or model-vs-motion alignment where screenshots alone are not enough.
npx skillsauth add affaan-m/everything-claude-code blender-motion-state-inspectionInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Do not judge animated 3D assets only from screenshots. Screenshots are review evidence, but they hide axis conventions, bone names, object scale, local transforms, parented meshes, material slots, and frame-by-frame contact state.
First extract structured Blender state, then use viewport screenshots or renders to confirm what the facts imply.
Inventory the scene.
Identify the skeleton.
Determine forward, up, and side axes.
Sample animation frames.
Check model integrity before retargeting blame.
Diagnose contact and motion issues.
Report facts before opinions.
## Blender Motion Inspection
### Scene Inventory
- Character candidates:
- Armatures:
- Helper/proxy objects:
- Cameras/lights:
### Orientation
- World up:
- Character forward:
- Root heading:
- Mirrored/backwards risk:
### Baseline Integrity
- Clean mesh bounds:
- Animated mesh bounds:
- Materials/skin preserved:
- Suspicious non-character meshes:
### Frame Findings
| Frame | Finding | Evidence |
| --- | --- | --- |
| 1 | Clean baseline pose | hips/spine/feet aligned |
| 96 | Foot penetrates floor | left_foot min_z = -0.04 |
### Verdict
- Pass/fail:
- Required fix:
- Render readiness:
Scenario: a retargeted character appears to skate during a walk cycle, but the front camera angle makes the foot contact hard to judge.
Apply the workflow:
HeroBody, armature HeroRig, ground plane Floor, no hidden proxy meshes.foot.L and foot.R; hips are pelvis; root bone is root.Extracted facts:
| Frame | Fact | Evidence |
| --- | --- | --- |
| 18 | Left foot is planted | foot.L min_z = 0.004, toe and heel both near floor |
| 24 | Left foot slides while planted | foot.L x = 0.21 -> 0.28 over six frames |
| 30 | Pelvis keeps moving forward | pelvis y = 1.14 -> 1.31 |
Verdict: fail for render readiness. The motion needs foot-lock cleanup or retargeting constraint review; the body mesh does not need proportion changes.
Scenario: a character looks correct in a still frame, but the animation moves opposite the expected travel direction.
Apply the workflow:
Extracted facts:
| Frame | Fact | Evidence |
| --- | --- | --- |
| 1 | Character face points toward world -Y | head/chest vector from neck to head resolves to -Y |
| 72 | Root motion travels toward world +Y | root y = 0.0 -> 2.8 |
| 72 | Feet remain visually forward-facing opposite travel | toe bones point -Y while displacement is +Y |
Verdict: likely backwards import or retargeting forward-axis mismatch. Fix the import/retarget axis mapping before editing animation curves.
If a Blender state exporter is available, prefer JSON that includes meshes, armatures, pose bones, materials, contacts, bounding boxes, and sampled animation frames. If no exporter exists, run a small Blender Python script through Blender itself, for example blender --background scene.blend --python collect_motion_state.py, because bpy is not available in a normal system Python interpreter.
development
Share durable, inspectable context and handoffs between Claude, Codex, Hermes, Cursor, OpenCode, and other agents through the local ECC Memory Vault. Use when an agent must save work state, transfer context, resume another agent's task, or search shared project knowledge.
development
Use when multiple consumers and providers must evolve an API or event schema without field drift, integration surprises, or one side silently redefining the interface.
tools
Query live GPU inventory, submit an authenticated Itô fixed-rate RFQ, inspect RFQ or procurement status, and run explicitly gated node qualification through the separately installed canonical CLI. Use when a user asks to find H100/H200 capacity, request a fixed compute rate, check Itô compute status, or validate GPU nodes.
data-ai
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination.