mcpbeat Sign in

Implementing Realtime Sync Skill for Cursor

Real-time communication patterns for live updates, collaboration, and presence. Use when building chat applications, collaborative tools, live dashboards, or streaming interfaces (LLM responses, metrics). Covers SSE (server-sent events for one-way streams), WebSocket (bidirectional communication), WebRTC (peer-to-peer video/audio), CRDTs (Yjs, Automerge for conflict-free collaboration), presence patterns, offline sync, and scaling strategies. Supports Python, Rust, Go, and TypeScript.

31k tokens
context cost
the whole folder, loaded on every use
13
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
394
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/ancoleman/ai-design-components --skill implementing-realtime-sync

The instruction itself

24 sections, as written by the author

Real-Time Sync

Implement real-time communication for live updates, collaboration, and presence awareness across applications.

When to Use

Use this skill when building:

  • LLM streaming interfaces - Stream tokens progressively (ai-chat integration)
  • Live dashboards - Push metrics and updates to clients
  • Collaborative editing - Multi-user document/spreadsheet editing with CRDTs
  • Chat applications - Real-time messaging with presence
  • Multiplayer features - Cursor tracking, live updates, presence awareness
  • Offline-first apps - Mobile/PWA with sync-on-reconnect

Protocol Selection Framework

Choose the transport protocol based on communication pattern:

Decision Tree

ONE-WAY (Server → Client only)
├─ LLM streaming, notifications, live feeds
└─ Use SSE (Server-Sent Events)
   ├─ Automatic reconnection (browser-native)
   ├─ Event IDs for resumption
   └─ Simple HTTP implementation

BIDIRECTIONAL (Client ↔ Server)
├─ Chat, games, collaborative editing
└─ Use WebSocket
   ├─ Manual reconnection required
   ├─ Binary + text support
   └─ Lower latency for two-way

COLLABORATIVE EDITING
├─ Multi-user documents/spreadsheets
└─ Use WebSocket + CRDT (Yjs or Automerge)
   ├─ CRDT handles conflict resolution
   ├─ WebSocket for transport
   └─ Offline-first with sync

PEER-TO-PEER MEDIA
├─ Video, screen sharing, voice calls
└─ Use WebRTC
   ├─ WebSocket for signaling
   ├─ Direct P2P connection
   └─ STUN/TURN for NAT traversal

Protocol Comparison

| Protocol | Direction | Reconnection | Complexity | Best For |

|----------|-----------|--------------|------------|----------|

| SSE | Server → Client | Automatic | Low | Live feeds, LLM streaming |

| WebSocket | Bidirectional | Manual | Medium | Chat, games, collaboration |

| WebRTC | P2P | Complex | High | Video, screen share, voice |

Implementation Patterns

Pattern 1: LLM Streaming with SSE

Stream LLM tokens progressively to frontend (ai-chat integration).

Python (FastAPI):

from sse_starlette.sse import EventSourceResponse

@app.post("/chat/stream")
async def stream_chat(prompt: str):
    async def generate():
        async for chunk in llm_stream:
            yield {"event": "token", "data": chunk.content}
        yield {"event": "done", "data": "[DONE]"}
    return EventSourceResponse(generate())

Frontend:

const es = new EventSource('/chat/stream')
es.addEventListener('token', (e) => appendToken(e.data))

Reference references/sse.md for full implementations, reconnection, and event ID resumption.

Pattern 2: WebSocket Chat

Bidirectional communication for chat applications.

Python (FastAPI):

connections: set[WebSocket] = set()

@app.websocket("/ws")
async def websocket_endpoint(websocket: WebSocket):
    await websocket.accept()
    connections.add(websocket)
    try:
        while True:
            data = await websocket.receive_text()
            for conn in connections:
                await conn.send_text(data)
    except WebSocketDisconnect:
        connections.remove(websocket)

Reference references/websockets.md for multi-language examples, authentication, heartbeats, and scaling.

Pattern 3: Collaborative Editing with CRDTs

Conflict-free multi-user editing using Yjs.

TypeScript (Yjs):

import * as Y from 'yjs'
import { WebsocketProvider } from 'y-websocket'

const doc = new Y.Doc()
const provider = new WebsocketProvider('ws://localhost:1234', 'doc-id', doc)
const ytext = doc.getText('content')

ytext.observe(event => console.log('Changes:', event.changes))
ytext.insert(0, 'Hello collaborative world!')

Reference references/crdts.md for conflict resolution, Yjs vs Automerge, and advanced patterns.

Pattern 4: Presence Awareness

Track online users, cursor positions, and typing indicators.

Yjs Awareness API:

const awareness = provider.awareness
awareness.setLocalState({ user: { name: 'Alice' }, cursor: { x: 100, y: 200 } })
awareness.on('change', () => {
  awareness.getStates().forEach((state, clientId) => {
    renderCursor(state.cursor, state.user)
  })
})

Reference references/presence-patterns.md for cursor tracking, typing indicators, and online status.

Pattern 5: Offline Sync (Mobile/PWA)

Queue mutations locally and sync when connection restored.

TypeScript (Yjs + IndexedDB):

import { IndexeddbPersistence } from 'y-indexeddb'
import { WebsocketProvider } from 'y-websocket'

const doc = new Y.Doc()
const indexeddbProvider = new IndexeddbPersistence('my-doc', doc)
const wsProvider = new WebsocketProvider('wss://api.example.com/sync', 'my-doc', doc)

wsProvider.on('status', (e) => {
  console.log(e.status === 'connected' ? 'Online' : 'Offline')
})

Reference references/offline-sync.md for conflict resolution and sync strategies.

Library Recommendations

Python

WebSocket:

  • websockets 13.x - AsyncIO-based, production-ready
  • FastAPI WebSocket - Built-in, dependency injection
  • Flask-SocketIO - Socket.IO protocol with fallbacks

SSE:

  • sse-starlette - FastAPI/Starlette, async, generator-based
  • Flask-SSE - Redis backend for pub/sub

Rust

WebSocket:

  • tokio-tungstenite 0.23 - Tokio integration, production-ready
  • axum WebSocket - Built-in extractors, tower middleware

SSE:

  • axum SSE - Native support, async streams

Go

WebSocket:

  • gorilla/websocket - Battle-tested, compression support
  • nhooyr/websocket - Modern API, context support

SSE:

  • net/http (native) - Flusher interface, no dependencies

TypeScript

WebSocket:

  • ws - Native WebSocket server, lightweight
  • Socket.io 4.x - Auto-reconnect, fallbacks, rooms
  • Hono WebSocket - Edge runtime (Cloudflare Workers, Deno)

SSE:

  • EventSource (native) - Browser-native, automatic retry
  • Node.js http (native) - Server-side, no dependencies

CRDT:

  • Yjs - Mature, TypeScript/Rust, rich text editing
  • Automerge - Rust/JS, JSON-like data, time-travel

Reconnection Strategies

SSE: Browser's EventSource handles reconnection automatically with exponential backoff.

WebSocket: Implement manual exponential backoff with jitter to prevent thundering herd.

Reference references/sse.md and references/websockets.md for complete implementation patterns.

Security Patterns

Authentication: Use cookie-based (same-origin) or token in Sec-WebSocket-Protocol header.

Rate Limiting: Implement per-user message throttling with sliding window.

Reference references/websockets.md for authentication and rate limiting implementations.

Scaling with Redis Pub/Sub

For horizontal scaling, use Redis pub/sub to broadcast messages across multiple backend servers.

Reference references/websockets.md for complete Redis scaling implementation.

Frontend Integration

React Hooks Pattern

SSE for LLM Streaming (ai-chat):

useEffect(() => {
  const es = new EventSource(`/api/chat/stream?prompt=${prompt}`)
  es.addEventListener('token', (e) => setContent(prev => prev + e.data))
  return () => es.close()
}, [prompt])

WebSocket for Live Metrics (dashboards):

useEffect(() => {
  const ws = new WebSocket('ws://localhost:8000/metrics')
  ws.onmessage = (e) => setMetrics(JSON.parse(e.data))
  return () => ws.close()
}, [])

Yjs for Collaborative Tables:

useEffect(() => {
  const doc = new Y.Doc()
  const provider = new WebsocketProvider('ws://localhost:1234', docId, doc)
  const yarray = doc.getArray('rows')
  yarray.observe(() => setRows(yarray.toArray()))
  return () => provider.destroy()
}, [docId])

Reference Documentation

For detailed implementation patterns, consult:

  • references/sse.md - SSE protocol, reconnection, event IDs
  • references/websockets.md - WebSocket auth, heartbeats, scaling
  • references/crdts.md - Yjs vs Automerge, conflict resolution
  • references/presence-patterns.md - Cursor tracking, typing indicators
  • references/offline-sync.md - Mobile patterns, conflict strategies

Example Projects

Working implementations available in:

  • examples/llm-streaming-sse/ - FastAPI SSE for LLM streaming (RUNNABLE)
  • examples/chat-websocket/ - Python FastAPI + TypeScript chat
  • examples/collaborative-yjs/ - Yjs collaborative editor

Testing Tools

Use scripts to validate implementations:

  • scripts/test_websocket_connection.py - WebSocket connection testing

Other skills for the same job

different authors, same section of the catalogue
D3 Viz
by chrisvoncsefalvay
×3

Creating interactive data visualisations using d3.js. This skill should be used when creating custom charts, graphs, network diagrams, geographic visualisations, or any complex SVG-based data visualisation that requires fine-grained control over visual elements, transitions, or interactions. Use this for bespoke visualisations beyond standard charting libraries, whether in React, Vue, Svelte, vanilla JavaScript, or any other environment.

20k tokens
Astropy
by christophacham
×3

Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.

16k tokens
Instrument Data To Allotrope
by anthropics
vendor ×2

Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production pipelines.

33k tokens scripts
Qutip
by ComeOnOliver
×2

Quantum mechanics simulations and analysis using QuTiP (Quantum Toolbox in Python). Use when working with quantum systems including: (1) quantum states (kets, bras, density matrices), (2) quantum operators and gates, (3) time evolution and dynamics (Schrödinger, master equations, Monte Carlo), (4) open quantum systems with dissipation, (5) quantum measurements and entanglement, (6) visualization (Bloch sphere, Wigner functions), (7) steady states and correlation functions, or (8) advanced methods (Floquet theory, HEOM, stochastic solvers). Handles both closed and open quantum systems across various domains including quantum optics, quantum computing, and condensed matter physics.

27k tokens
Copilot Usage Metrics
by github
vendor ×1

Retrieve and display GitHub Copilot usage metrics for organizations and enterprises using the GitHub CLI and REST API.

1k tokens scripts
Mentoring Juniors
by github
vendor ×1

Socratic mentoring for junior developers and AI newcomers. Guides through questions, never answers. Triggers: "help me understand", "explain this code", "I''m stuck", "Im stuck", "I''m confused", "Im confused", "I don''t understand", "I dont understand", "can you teach me", "teach me", "mentor me", "guide me", "what does this error mean", "why doesn''t this work", "why does not this work", "I''m a beginner", "Im a beginner", "I''m learning", "Im learning", "I''m new to this", "Im new to this", "walk me through", "how does this work", "what''s wrong with my code", "what''s wrong", "can you break this down", "ELI5", "step by step", "where do I start", "what am I missing", "newbie here", "junior dev", "first time using", "how do I", "what is", "is this right", "not sure", "need help", "struggling", "show me", "help me debug", "best practice", "too complex", "overwhelmed", "lost", "debug this", "/socratic", "/hint", "/concept", "/pseudocode". Progressive clue systems, teaching techniques, and success metrics.

4k tokens
Astropy
by K-Dense-AI
×1

Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.

18k tokens
Polars
by K-Dense-AI
×1

High-performance DataFrame library for Python ETL, analytics, and pandas migration. Use for expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU execution.

20k tokens

How to use it

Copy the folder

Take ancoleman/implementing-realtime-sync from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.