blockout-model

blockout-model is a skill for Claude Code, Codex from w1ne/kernelCAD-web. It costs 46 tokens per session (1,188 once invoked), scanned A, original, MIT.

A method for making a rough, adjustable 3D model of an object's main shapes before adding fine detail. A blockout tests whether the object's outline matches a reference image from key views.

In plain words
What is it for?
Use it to define adjustable dimensions, place a reference image, and check a model's silhouette from canonical views.
Why use it?
It catches incorrect proportions early, when changing the main shape is easier than revising a detailed model.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to define adjustable dimensions, place a reference image, and check a model's silhouette from canonical views.

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Install with agentmods
npx agentmods add skills/w1ne/kernelcad-web/blockout-model
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add w1ne/kernelCAD-web --skill blockout-model
Clone the repo
git clone --depth 1 https://github.com/w1ne/kernelCAD-web

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for blockout-model

README.md
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Your own site
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Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for blockout-model

Your own site · 80×15
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Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,188 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00046 $0.01188
Opus 5.5 $0.00018 $0.00475
Sonnet 5.5 $0.00009 $0.00238
Haiku 4.5 $0.00005 $0.00119

Measured 1mo ago against content hash 2895052b25f0, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

blockout-model scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

src/agent/skills/kernelcad-from-reference/blockout-model/SKILL.md · 135 lines

How it starts

The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.

blockout-model

Purpose

The blockout pass produces a coarse, parametric approximation of the object's primary masses. It is not a finished model — it is a testable hypothesis: "does this bounding envelope match the reference silhouette in all canonical views?" Only after the blockout is plausible does detail work begin.

Inputs

  • The // Real Object Brief from prepare-prompt/SKILL.md.
  • The reference photo path.

What to do

Step 1 — Declare key params

Map each dimension in the brief's Scale section to a param(). Use the brief's estimated value as the default:

const frameW  = param('frameWidth',  130, { min: 100, max: 160, description: 'outer frame width mm' });
const frameH  = param('frameHeight',  48, { min: 30,  max: 70  });
const bodyD   = param('bodyDepth',     5, { min: 2,   max: 12  });
const bridgeW = param('bridgeWidth',  18, { min: 10,  max: 30  });

All key dimensions must be params, not magic numbers. The blockout must be adjustable after the first canonical-view check without touching geometry code.

Step 2 — Place the reference image overlay

Pick the view plane that shows the most information. For most flat products, the front view is the XZ plane:

referenceImage('./reference.jpg', {
  plane: 'xz',
  anchor: 'origin',
  scale: 'fit-bbox',
  opacity: 0.35,
});

The reference image does not affect the score (it is hidden during scoring). It is for visual alignment during authoring.

Step 3 — Build primary mass boxes

One box() or extrudeRoundedRect() per major component. No holes, no features, no material yet. Translate each into position. For symmetric objects, build one half only and call .mirror() after the blockout check:

// primary lens+frame slab
const frameBody = extrudeRoundedRect(frameW, frameH, bodyD, 4)
  .translate(-frameW / 2, 0, -frameH / 2);

// arm stubs — one side, to be mirrored
const armStub = box(50, armW, armT)
  .translate(frameW / 2, 0, -armT / 2);

const full = frameBody.union(armStub.mirror('YZ'));
return full;

Read the full file on GitHub · 135 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 135 lines · 46 tokens per session scan A 2895052b25f0

Subscribe to this mod's changes

blockout-model is a skill published in the GitHub repository w1ne/kernelCAD-web (33 stars, last pushed today), licensed MIT. It adds 46 tokens to every session and 1,188 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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