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skill CX Codex

reference-analysis-validator — Claude Code skill: validate 3D

The skill measures reference images and Blender renders and blocks a 1:1 claim until the metrics pass.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add RobLe3/cc-blender-skill --skill reference-analysis-validator -a claude-code
Open on GitHub

What reference-analysis-validator does

This skill turns "looks close" into measurable gates. It classifies sources — front, side, back, top, texture atlas, decals, maps, lightmap, aura, context — and builds reference_manifest.json with hard expected part counts and view roles. Masks and components are extracted from each source, then the model is rendered from a matching orthographic camera with reference planes hidden.

Comparison runs through scripts/render_overlay_validator.py: IoU, SSIM, centroid and bbox drift, plus landmark drift for face, eyes and smile. Default gates: exact structural part count, front silhouette IoU at or above 0.90 for rigid and logotype shapes, 0.82 for a first mascot pass, bbox center drift within 12 px at 1024 px validation size, bbox size drift within 3% of image dimension, landmark drift within 2%. If hard gates fail, final export is refused.

One catch: compare like with like. A wireframe edge mask against a shaded beauty render gives a misleadingly low IoU, so for hard gates render a flat silhouette or matte pass, and use render_overlay_validator.py --reference-mode ... --render-mode ... when source and render need different extraction modes. Before the first Blender call, read ../text-to-blender/references/mcp-backends.md and pick an MCP backend — official is preferred for shared capabilities, but the chosen one stays for the whole task.

What it helps with

  • build a source manifest with expected part counts
  • measure IoU and SSIM between reference and render
  • catch centroid and bbox drift before export
  • compare wireframe masks against a render silhouette in one mode
  • refuse export until hard gates pass

Example prompts for the agent

  • check the references and build reference_manifest.json before modeling
  • compare the reference mask with the render using render_overlay_validator.py
  • compute front silhouette IoU and show the report

How to install reference-analysis-validator

1Skills CLI (Vercel)

npx skills add RobLe3/cc-blender-skill --skill reference-analysis-validator -a claude-code

2Manually: put the files in place

~/.claude/skills/reference-analysis-validator/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/reference-analysis-validator/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about reference-analysis-validator

How do I install reference-analysis-validator in Claude?

Run npx skills add RobLe3/cc-blender-skill --skill reference-analysis-validator -a claude-code. The skill lands in ~/.claude/skills/reference-analysis-validator/SKILL.md.

What does reference-analysis-validator do?

It extracts masks and components from reference images and Blender renders, then compares them by IoU, SSIM, centroid and bounding boxes. Final export is blocked until the hard gates pass.

What does the skill need to run?

Blender access through an MCP server and a read of ../text-to-blender/references/mcp-backends.md before the first call. It works with scripts/reference_manifest_compiler.py and scripts/render_overlay_validator.py.

Source text

SKILL.md · MIT
---
name: reference-analysis-validator
description: Measure and validate supplied reference images, wireframes, texture atlases, and Blender renders before declaring a reconstruction 1:1. Use when an asset must match a template, when visual feedback says the output is off, when part counts must be exact, or before exporting a brand mascot/logo reconstruction. Pairs with reference-to-3d, contour-to-mesh, orthographic-registration, atlas-uv-fitting, and Blender MCP.
allowed-tools: Read Bash Glob Grep mcp__blender__execute_blender_code mcp__blender__get_scene_info mcp__blender__get_object_info mcp__blender__get_objects_summary mcp__blender__get_object_detail_summary mcp__blender__render_viewport_to_path mcp__blender__search_api_docs mcp__blender_official__execute_blender_code mcp__blender_official__get_objects_summary mcp__blender_official__get_object_detail_summary mcp__blender_official__render_viewport_to_path mcp__blender_official__search_api_docs
---


## MCP backend

Use when: Any 1:1 reference/model validation task involving masks, overlays, part counts, centroids, bounding boxes, SSIM/IoU, source manifests, or fail-before-export gates.

Before the first Blender call, read [../text-to-blender/references/mcp-backends.md](../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.
# Reference Analysis Validator

This skill converts “looks close” into measurable gates. For brand/logo/mascot work, **do not model or export until a source manifest and validation thresholds exist**.

## Required outputs

Create these in the asset output folder:

- `reference_manifest.json` — classified source files, expected parts, thresholds.
- `source_analysis/*.json` — image metadata, masks/components/landmarks.
- `validation/front_overlay_reference.png` — reference and render overlay.
- `validation/front_mask_validation.json` — IoU/SSIM/bbox/centroid report.

## Workflow

1. Classify sources: front, side, back, top, texture atlas, decals, maps, lightmap, aura/context.
2. Build/refresh `reference_manifest.json` with hard expected counts and view roles.
3. Extract masks/components from each source using `scripts/reference_manifest_compiler.py` or existing analyzers.
4. Render model from matching orthographic camera with reference planes hidden.
5. Compare reference mask vs render mask using `scripts/render_overlay_validator.py`.
6. Refuse final export if hard gates fail.

## Modality rule

Compare like with like. A wireframe edge mask compared against a shaded beauty render gives misleadingly low IoU. For hard gates, render a flat silhouette/matte pass from Blender or compare reference edges to render edges. Use `render_overlay_validator.py --reference-mode ... --render-mode ...` when the source and render need different mask extraction modes.

## Default validation gates

- primary structural part count: exact.
- front silhouette IoU: target >= 0.90 for rigid/logotype shapes; >= 0.82 acceptable for first mascot reconstruction pass.
- bbox center drift: <= 12 px at 1024 px validation size.
- bbox size drift: <= 3% of image dimension.
- face/eye/smile landmark drift: <= 2% of image dimension when landmarks are defined.

## Failure policy

If a repeated mismatch occurs, record the measured failure, then route to the missing specialty skill:

- wrong silhouette → `contour-to-mesh`
- wrong depth/side/back → `orthographic-registration`
- wrong textures → `atlas-uv-fitting`
- wrong whole workflow → `mascot-logo-reconstruction`

## Read when needed

- `references/metrics-and-thresholds.md` for metric definitions and recommended gates.

## Sources distilled

Official/library docs to prefer while extending this skill:

- OpenCV contour features: moments, area, perimeter, bounding rectangles.
- OpenCV shape matching / Hu moments.
- OpenCV homography and geometric transforms.
- scikit-image SSIM for perceptual comparison.

© RobLe3 · MIT · RobLe3/cc-blender-skill

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