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.
npx skills add daffy0208/ai-dev-standards --skill spatial-developergit clone --depth 1 https://github.com/daffy0208/ai-dev-standardsWrote 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.
[](https://agentmods.dev/skills/daffy0208/ai-dev-standards/spatial-developer)<a href="https://agentmods.dev/skills/daffy0208/ai-dev-standards/spatial-developer"><img src="https://agentmods.dev/badge/skills/daffy0208/ai-dev-standards/spatial-developer/github.svg" alt="Measured on agentmods" height="20"></a>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.
<a href="https://agentmods.dev/skills/daffy0208/ai-dev-standards/spatial-developer"><img src="https://agentmods.dev/badge/skills/daffy0208/ai-dev-standards/spatial-developer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00022 | $0.01310 |
| Opus 5.5 | $0.00009 | $0.00524 |
| Sonnet 5.5 | $0.00004 | $0.00262 |
| Haiku 4.5 | $0.00002 | $0.00131 |
Grade A, and why
spatial-developer 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.
How it starts
The opening of the file, as written. The whole thing — 277 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spatial Developer Skill
I help you build AR/VR experiences, spatial interfaces, and immersive 3D applications.
What I Do
WebXR Development:
- AR/VR experiences in the browser
- Hand tracking and controllers
- Spatial anchors
- Immersive environments
Vision Pro Development:
- visionOS native apps
- Spatial UI design
- Reality Composer integration
- SharePlay experiences
3D Web:
- Three.js scenes
- React Three Fiber
- 3D interactions
- Spatial audio
WebXR Basics
npm install three @react-three/fiber @react-three/drei @react-three/xr
Simple VR Scene
// components/VRScene.tsx
'use client'
import { Canvas } from '@react-three/fiber'
import { VRButton, XR, Controllers, Hands } from '@react-three/xr'
import { Box, OrbitControls } from '@react-three/drei'
export function VRScene() {
return (
<>
<VRButton />
<Canvas>
<XR>
<ambientLight intensity={0.5} />
<pointLight position={[10, 10, 10]} />
{/* 3D Content */}
<Box position={[0, 1, -2]} args={[1, 1, 1]}>
<meshStandardMaterial color="hotpink" />
</Box>
{/* VR Controllers */}
<Controllers />
{/* Hand Tracking */}
<Hands />
</XR>
</Canvas>
</>
)
}
AR on Web (WebXR)
// components/ARScene.tsx
'use client'
import { Canvas } from '@react-three/fiber'
import { ARButton, XR } from '@react-three/xr'
import { useState } from 'react'
export function ARScene() {
const [hitTest, setHitTest] = useState(null)
return (
<>
<ARButton
sessionInit={{
requiredFeatures: ['hit-test'],
optionalFeatures: ['dom-overlay']
}}
/>
<Canvas>
<XR
onHitTest={(hitMatrix, hit) => {
setHitTest(hit)
}}
>
<ambientLight />
{hitTest && (
<mesh position={hitTest.position}>
<sphereGeometry args={[0.1]} />
<meshStandardMaterial color="blue" />
</mesh>
)}
</XR>
</Canvas>
</>
)
}
What ships with it
2 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.
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.
- 1mo ago First seen · 277 lines · 22 tokens per session scan A 32cb6a80a36d
spatial-developer is a skill published in the GitHub repository daffy0208/ai-dev-standards (38 stars, last pushed 10mo ago), licensed MIT. It adds 22 tokens to every session and 1,310 once invoked, about $0.0001 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 2026-09-03.
Other skills, from other repositories
xr-engineer
!cat skills/shared/protocols/3d-spatial-foundations.md 2>/dev/null || true !cat skills/shared/game-visual-foundations.md 2>/dev/null || echo "=== Visual Foundations not loaded ===" !cat skills/shared/protocols/ux-protocol.md 2>/dev/null || true !cat skills/shared/protocols/game-test-protocol.md 2>/dev/null || true…
metaverse-expert
Create production-ready metaverse experiences including VR/AR applications, virtual worlds, social platforms, and blockchain-integrated digital assets. Use when the user mentions VR/AR/XR, virtual worlds, spatial computing, 3D avatars and scenes, Unity or Unreal for immersive apps, or NFT-backed digital assets.
AR/VR Application Testing
Testing augmented and virtual reality applications including spatial tracking, gesture recognition, performance on headsets, and motion sickness testing.
motion
Reconstruct a skeleton from calibrated mesh projections and sequential VLM joint annotations, then fit joints and skin weights. Generate motion from joint-position trajectories, rhythm and contact constraints through IK; refine bone orientation against the action, then export, retarget and validate on the target mesh.
3d_object
Judge whether a generated mesh is fit to ship in a browser game, from the same rendered sheet the orientation review uses.
3d_scene
Choose how to build a 3dscene asset. Do not default to one pipeline for every task: what the user specified about the scene's appearance matters more than the scene type, and generative reconstruction is the least stable route here.