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Reference Look Calibration

Community
RobLe3
reference-look-calibration

Calibrate Blender materials, lighting, camera crop, emission/glow, color management, and aura/HUD styling against supplied original/reference images using measurable color, brightness, saturation, bbox, and mask statistics. Use when a product must match the lighting/look of a source image or when audits say the product is too bright, desaturated, wrong hue, wrong glow, or wrong silhouette extent.

Overview

PublisherRobLe3
Repositorycc-blender-skill
Skill namereference-look-calibration
Stars
131
Forks
14
Bundled files
1
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by RobLe3 on GitHub. Read the source before you install it.

Installation

Install the Reference Look Calibration AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/RobLe3/cc-blender-skill/tree/main/plugin/skills/reference-look-calibration
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/RobLe3/cc-blender-skill.git /tmp/cc-blender-skill
mkdir -p .claude/skills
cp -r /tmp/cc-blender-skill/plugin/skills/reference-look-calibration .claude/skills/reference-look-calibration
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Reference Look Calibration in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Reference Look Calibration on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Reference Look Calibration is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

MCP backend

Use when: Reference-based look-dev, lighting/material/color calibration, original-image visual matching, glow/aura/HUD matching, HSV/brightness/mask fit reports, final look pass after geometry and UV are locked.

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.

Reference Look Calibration

This skill handles the final visual match after geometry and UVs are locked. It must not compensate for wrong shape, wrong UVs, or wrong camera framing.

Inputs

  • accepted geometry / UV fit reports;
  • reference/original image(s);
  • product preview render(s);
  • optional mask overlays and multiview fit reports.

Metrics

Use scripts/look_fit_report.py to compare:

  • object/bright-mask IoU and bbox extent;
  • configured hue-band mask IoU for glow/accent assets;
  • mean/std HSV and BGR under object mask;
  • brightness p95 / mean;
  • saturation mean;
  • hue drift.

Calibration order

  1. Camera crop / orthographic scale — object extent must match before color tuning.
  2. World/background darkness.
  3. Base material hue/value/saturation.
  4. Emission strength and glow color.
  5. Aura/HUD ring color and thickness.
  6. Color management / exposure / gamma.
  7. Final render overlay and metrics.

Hard rules

  • Do not tune lighting before geometry/UV fit gates pass.
  • Do not change accent/glow hue away from the source reference unless the user explicitly asks.
  • Do not hide mismatched geometry with bloom, fog, or overexposure.
  • Write look metrics before and after calibration.

Handoff

Consumes validation/multiview_fit_report*.json and product previews. Produces validation/look_fit_report.json, look overlays, and updated material/light/render settings.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Reference Look Calibration AI skill do?

Calibrate Blender materials, lighting, camera crop, emission/glow, color management, and aura/HUD styling against supplied original/reference images using measurable color, brightness, saturation, bbox, and mask statistics. Use when a product must match the lighting/look of a source image or when audits say the product is too bright, desaturated, wrong hue, wrong glow, or wrong silhouette extent.

Why use Reference Look Calibration on TypingMind?

Because you install it once and use it with any model. Reference Look Calibration is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Reference Look Calibration in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/RobLe3/cc-blender-skill/tree/main/plugin/skills/reference-look-calibration. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Reference Look Calibration?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Reference Look Calibration?

As many as you like. As long as a model supports skills, you can use Reference Look Calibration with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Reference Look Calibration AI skill free?

Yes. It is published on GitHub by RobLe3 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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