The root component that creates the physics world.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionr3f-physicsExecute the skills CLI command in your project's root directory to begin installation:
Fetches r3f-physics 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-physics. Access via /r3f-physics 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 { Physics, RigidBody, CuboidCollider } from '@react-three/rapier'
import { Suspense } from 'react'
function Scene() {
return (
<Canvas>
<Suspense fallback={null}>
<Physics debug>
{/* Falling box */}
<RigidBody>
<mesh>
<boxGeometry />
<meshStandardMaterial color="orange" />
</mesh>
</RigidBody>
{/* Static ground */}
<CuboidCollider position={[0, -2, 0]} args={[10, 0.5, 10]} />
</Physics>
</Suspense>
<ambientLight />
<directionalLight position={[5, 5, 5]} />
</Canvas>
)
}
npm install @react-three/rapier
The root component that creates the physics world.
import { Physics } from '@react-three/rapier'
<Canvas>
<Suspense fallback={null}>
<Physics
gravity={[0, -9.81, 0]} // Gravity vector
debug={false} // Show collider wireframes
timeStep={1/60} // Fixed timestep (or "vary" for variable)
paused={false} // Pause simulation
interpolate={true} // Smooth rendering between physics steps
colliders="cuboid" // Default collider type for all RigidBodies
updateLoop="follow" // "follow" (sync with frame) or "independent"
>
{/* Physics objects */}
</Physics>
</Suspense>
</Canvas>
For performance optimization with static scenes:
<Canvas frameloop="demand">
<Physics updateLoop="independent">
{/* Physics only triggers render when bodies are active */}
</Physics>
</Canvas>
Makes objects participate in physics simulation.
import { RigidBody } from '@react-three/rapier'
// Dynamic body (affected by forces/gravity)
<RigidBody>
<mesh>
<boxGeometry />
<meshStandardMaterial color="red" />
</mesh>
</RigidBody>
// Fixed body (immovable)
<RigidBody type="fixed">
<mesh>
<boxGeometry args={[10, 0.5, 10]} />
<meshStandardMaterial color="gray" />
</mesh>
</RigidBody>
// Kinematic body (moved programmatically)
<RigidBody type="kinematicPosition">
<mesh>
<sphereGeometry />
<meshStandardMaterial color="blueMake 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
Registry listing for r3f-physics matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in r3f-physics — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend r3f-physics for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
r3f-physics reduced setup friction for our internal harness; good balance of opinion and flexibility.
r3f-physics fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
r3f-physics reduced setup friction for our internal harness; good balance of opinion and flexibility.
r3f-physics is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
I recommend r3f-physics for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
I recommend r3f-physics for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
r3f-physics fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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