calibrate-model

calibrate-model is a skill for Claude Code, Codex from playcanvas/create-playcanvas. It costs 44 tokens per session (746 once invoked), scanned A, original, MIT.

A workflow for measuring 3D GLB model files once and recording their size, floor offset, and facing direction for PlayCanvas projects.

In plain words
What is it for?
It helps calibrate characters, buildings, vehicles, and other GLB assets before adding many copies to a game scene.
Why use it?
It prevents models from appearing at inconsistent sizes, floating above the ground, sinking into it, or facing the wrong way when placed repeatedly.

Skill for Claude CodeCodex

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

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.

agentmods
npx agentmods add skills/playcanvas/create-playcanvas/calibrate-model
Any agent
npx skills add playcanvas/create-playcanvas --skill calibrate-model
Clone the repo
git clone --depth 1 https://github.com/playcanvas/create-playcanvas

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 calibrate-model

README.md
[![agentmods](https://agentmods.dev/badge/skills/playcanvas/create-playcanvas/calibrate-model.svg)](https://agentmods.dev/skills/playcanvas/create-playcanvas/calibrate-model)
Your own site
<a href="https://agentmods.dev/skills/playcanvas/create-playcanvas/calibrate-model"><img src="https://agentmods.dev/badge/skills/playcanvas/create-playcanvas/calibrate-model.svg" alt="Measured on agentmods" height="20"></a>
Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 746 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00044 $0.00746
Opus 5 $0.00022 $0.00373
Sonnet 5 $0.00009 $0.00149
Haiku 4.5 $0.00004 $0.00075

Measured 6d ago against content hash f2297806f5d8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

calibrate-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 6d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/calibrate-model/SKILL.md · 66 lines

How it starts

The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Model calibration

Use the inspect-glb skill to measure every unique GLB before mass placement. Rely on dims and groundOffset for contact-accurate placement only when it reports boundsSource: vertices. Store one tuning record per asset:

const ASSET_TUNING = {
    model: {
        boundsSource: 'vertices',
        aabb: { min: [-4, -1, -9], max: [4, 6, 9] },
        dims: [8, 7, 18],
        center: [0, 2.5, 0],
        groundOffset: 1,
        intended: { dimension: 'length', size: 18 },
        scale: 0.9,
        y: 0.9,
        yaw: 180
    }
} as const;

Calculate the record

  1. Pick and record the intended dimension and size: character height, building footprint, or vehicle length. Base it on world units or an already calibrated reference model.
  2. Calculate scale = intendedSize / measuredDimension.
  3. For a floor-resting model, calculate y = groundOffset * scale. Record a deliberate offset for waterlines, embedded objects, or airborne models.
  4. Confirm directional facing once in the running app, as the apply-conventions skill describes. PlayCanvas entities face -Z while glTF convention is +Z, but asset packs vary.
  5. Retain boundsSource, aabb, dims, center, groundOffset, and the intended size with { scale, y, yaw }. Use the scaled footprint and centre for initial spacing; do not re-derive or add per-instance nudges.

Keep gameplay position and heading on an outer semantic root, and seat the model on one predictable reference point beneath it so a root position means the same thing for every asset: by default the footprint centre over the base. Apply the authored yaw on a wrapper, then the scale and the full offset on the render child inside it, so an off-centre pivot is compensated in the authored frame and never re-rotated by the yaw or by gameplay heading:

const yaw = new Entity('yaw');
yaw.setLocalEulerAngles(0, t.yaw, 0);
const visual = instantiate(asset);
visual.setLocalScale(t.scale, t.scale, t.scale);
visual.setLocalPosition(-t.center[0] * t.scale, t.y, -t.center[2] * t.scale);
yaw.addChild(visual);
root.addChild(yaw);

Read the full file on GitHub · 66 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 6d ago First seen · 66 lines · 44 tokens per session scan A f2297806f5d8

Subscribe to this mod's changes

calibrate-model is a skill published in the GitHub repository playcanvas/create-playcanvas (53 stars, last pushed yesterday), licensed MIT. It adds 44 tokens to every session and 746 once invoked, about $0.0002 per session on Opus 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.

Related

Other skills, from other repositories

gameobject-component-destroy

Destroy one or more Components from a target GameObject. Missing (null) components are skipped — they cannot be destroyed. Use 'gameobject-find' and 'gameobject-component-get' to identify the components first.

IvanMurzak/Unity-MCP · 49 tokens

unity-version-split

Split a C# file into Unity 6.5+ and pre-Unity 6.5 variants. Use when a file needs different implementations for different Unity versions due to API changes (e.g., EntityId vs int, GetEntityId vs GetInstanceID).

IvanMurzak/Unity-MCP · 59 tokens

playtest-report

Generates a structured playtest report template or analyzes existing playtest notes into a structured format. Use this to standardize playtest feedback collection and analysis.

Donchitos/Claude-Code-Game-Studios · 35 tokens

unity-manual-component

Manually add, configure, reorder, and copy components on GameObjects using Unity Editor UI. For one-off Inspector workflows that do not need REST automation.

Besty0728/Unity-Skills · 36 tokens

godot-signals-groups

Build event-driven, decoupled Godot 4.7 gameplay with signals and node groups: declare and emit custom signals, connect with Callables (incl. bind/one-shot), and broadcast to many nodes via groups and callgroup. Use when wiring node communication in a Godot project, replacing tight references with signals…

gamedev-skills/awesome-gamedev-agent-skills · 95 tokens

threejs-exposure-color-grading

Build a measured exposure and grading path in Three.js. Use for a 64x36 encoded luminance meter, asynchronous readback, weighted log-average exposure, asymmetric adaptation, single tone-map ownership, and a generated 32-cube post-tone-map LUT.

scottstts/Threejs-Awesome-Graphics-Agent-Skills · 60 tokens