accessibility
Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when…
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 -y skills add affaan-m/everything-claude-code --skill blender-motion-state-inspection --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/blender-motion-state-inspectionContext preview
The summary Claude sees to decide when to auto-load this skill.
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.
name: blender-motion-state-inspection description: 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. metadata: origin: ECC tools: Read, Write, Edit, Bash, Grep, Glob
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.
1. Establish the clean scene and asset baseline before judging motion. 2. Extract structured facts from Blender using an exporter or Blender Python run inside Blender's own interpreter. 3. Sample the frames most likely to expose contact, orientation, scale, and retargeting errors. 4. Compare the measured facts against the user's expected pose, direction, ground plane, and render goal. 5. Return a concise report that separates confirmed facts, likely causes, and required fixes.
1. Inventory the scene.
2. Identify the skeleton.
3. Determine forward, up, and side axes.
4. Sample animation frames.
5. Check model integrity before retargeting blame.
6. Diagnose contact and motion issues.
7. 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:
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:
Your agent can write code, but ECC gives it a coordinated engineering system and toolbox: it plans before it builds, verifies changes with tests, reviews its own work from a fresh context, remembers what matters, and turns repeated wins into reusable skills
Repo: affaan-m/everything-claude-code
Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when…
Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures,…
Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when…
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent's…
Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails…
Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer…