Core React Three Fiber setup with Canvas, hooks, JSX elements, and event handling.
Works with
Canvas component creates the WebGL context, scene, camera, and renderer with configurable settings for shadows, color management, frame loop control, and event handling
useFrame hook subscribes to the render loop with access to state (clock, pointer, camera), delta time, and priority-based execution ordering
useThree hook provides selective access to R3F state including camera, renderer, scene, raycast
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionr3f-fundamentalsExecute the skills CLI command in your project's root directory to begin installation:
Fetches r3f-fundamentals from enzed/r3f-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate r3f-fundamentals. Access via /r3f-fundamentals in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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import { Canvas } from '@react-three/fiber'
import { useRef } from 'react'
import { useFrame } from '@react-three/fiber'
function RotatingBox() {
const meshRef = useRef()
useFrame((state, delta) => {
meshRef.current.rotation.x += delta
meshRef.current.rotation.y += delta * 0.5
})
return (
<mesh ref={meshRef}>
<boxGeometry args={[1, 1, 1]} />
<meshStandardMaterial color="hotpink" />
</mesh>
)
}
export default function App() {
return (
<Canvas camera={{ position: [0, 0, 5], fov: 75 }}>
<ambientLight intensity={0.5} />
<directionalLight position={[5, 5, 5]} />
<RotatingBox />
</Canvas>
)
}
The root component that creates the WebGL context, scene, camera, and renderer.
import { Canvas } from '@react-three/fiber'
function App() {
return (
<Canvas
// Camera configuration
camera={{
position: [0, 5, 10],
fov: 75,
near: 0.1,
far: 1000,
}}
// Or use orthographic
orthographic
camera={{ zoom: 50, position: [0, 0, 100] }}
// Renderer settings
gl={{
antialias: true,
alpha: true,
powerPreference: 'high-performance',
preserveDrawingBuffer: true, // For screenshots
}}
dpr={[1, 2]} // Pixel ratio min/max
// Shadows
shadows // or shadows="soft" | "basic" | "percentage"
// Color management
flat // Disable automatic sRGB color management
// Frame loop control
frameloop="demand" // 'always' | 'demand' | 'never'
// Event handling
eventSource={document.getElementById('root')}
eventPrefix="client" // 'offset' | 'client' | 'page' | 'layer' | 'screen'
// Callbacks
onCreated={(state) => {
console.log('Canvas ready:', state.gl, state.scene, state.camera)
}}
onPointerMissed={() => console.log('Clicked background')}
// Styling
style={{ width: '100%', height: '100vh' }}
>
<Scene />
</Canvas>
)
}
R3F sets sensible defaults:
Subscribe to the render loop. Called every frame (typically 60fps).
import { useFrame } from '@react-three/fiber'
import { useRef } from 'react'
function AnimatedMesh() {
const meshRef = useRef()
useFrame((state, delta, xrFrame) => {
// state: Full R3F state (see useThree)
// delta: Time since last frame in seconds
// xrFrame: XR frame if in VR/AR mode
// Animate rotation
meshRef.current.Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
r3f-fundamentals has been reliable in day-to-day use. Documentation quality is above average for community skills.
r3f-fundamentals fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Keeps context tight: r3f-fundamentals is the kind of skill you can hand to a new teammate without a long onboarding doc.
Useful defaults in r3f-fundamentals — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: r3f-fundamentals is focused, and the summary matches what you get after install.
r3f-fundamentals is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
r3f-fundamentals is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
r3f-fundamentals reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for r3f-fundamentals matched our evaluation — installs cleanly and behaves as described in the markdown.
Solid pick for teams standardizing on skills: r3f-fundamentals is focused, and the summary matches what you get after install.
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