
3D Wood Lighting Scorecard
Light carved wood in three.js and score the render out of 10 against a fixed rubric, iterating until it passes.
- Repository
- MengTo/Skills
- Stars
- 7,187
- Licence
- MIT
- Files
- 7 files
What it does
When installed, the agent can build a lit 3D wood scene in three.js (a web 3D library) with procedural grain, a single window as the main light, soft shadows, light shafts and dust. It then renders the scene in a headless browser, measures the image with a fixed set of metrics, scores it out of 10 against a written rubric, and adjusts the lighting until each item reaches a target score. It is a specialised lighting and material workflow, not a general 3D tool.
Great for
- Developers building web 3D scenes in three.js who want realistic wood, timber or joinery rendering
- Designers or artists who want measurable, repeatable feedback on a render rather than subjective judgement
- Anyone who wants an agent to iterate on a lighting setup against numeric targets
Skip it if
- Users who do not run three.js or WebGL projects, since the output is code for that stack
- Projects needing scanned or painted PBR texture pipelines, which the skill points to a different skill for; this one uses procedural wood
- Running scorecard.mjs on untrusted pages or machines, because it launches a headless browser and executes the bundled scripts
Try asking
- “Make this oiled oak workshop bench look like real wood under a window light and score it out of 10”
- “Get the lighting on this kumiko screen to 8 and show me the scorecard”
- “Fix the washed-out grain on this timber scene and check the black point stays low”
Install in 3 steps
- 1
Download the skill
The ZIP contains the 7 original files, the MIT licence and an attribution note.
3d-wood-lighting-scorecard.zip - 2
Add it to your agent
Claude Code (all projects)
mkdir -p ~/.claude/skills && unzip 3d-wood-lighting-scorecard.zip -d ~/.claude/skills/Claude Code / Agent SDK (this project only)
mkdir -p .claude/skills && unzip 3d-wood-lighting-scorecard.zip -d .claude/skills/Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.
- 3
Ask for the task
No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.
Get better results
- Run scorecard.mjs with --target and --out to get a JSON report and a non-zero exit code when items fall short
- Review the rubric in references/rubric.md so you know what each score anchor means before trusting the number
- Run the scorecard headless only; the in-app preview is not suitable for measurement
What's inside
- agents/openai.yaml
- PROMPT.md
- references/last-scorecard.json
- references/metrics.js
- references/rubric.md
- references/scorecard.mjs
- SKILL.md
Redistributed unmodified from MengTo/Skills under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.