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Websocket Engineer

CommunityPopular
Jeffallan
websocket-engineer

Use when building real-time communication systems with WebSockets or Socket.IO. Invoke for bidirectional messaging, horizontal scaling with Redis, presence tracking, room management.

Overview

PublisherJeffallan
Repositoryclaude-skills
Skill namewebsocket-engineer
Stars
11.7K
Forks
1.1K
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Jeffallan on GitHub. Read the source before you install it.

Installation

Install the Websocket Engineer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Jeffallan/claude-skills/tree/main/skills/websocket-engineer
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Jeffallan/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/skills/websocket-engineer .claude/skills/websocket-engineer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Websocket Engineer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Websocket Engineer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Websocket Engineer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

WebSocket Engineer

Core Workflow

  1. Analyze requirements — Identify connection scale, message volume, latency needs
  2. Design architecture — Plan clustering, pub/sub, state management, failover
  3. Implement — Build WebSocket server with authentication, rooms, events
  4. Validate locally — Test connection handling, auth, and room behavior before scaling (e.g., npx wscat -c ws://localhost:3000); confirm auth rejection on missing/invalid tokens, room join/leave events, and message delivery
  5. Scale — Verify Redis connection and pub/sub round-trip before enabling the adapter; configure sticky sessions and confirm with test connections across multiple instances; set up load balancing
  6. Monitor — Track connections, latency, throughput, error rates; add alerts for connection-count spikes and error-rate thresholds

Reference Guide

Load detailed guidance based on context:

TopicReferenceLoad When
Protocolreferences/protocol.mdWebSocket handshake, frames, ping/pong, close codes
Scalingreferences/scaling.mdHorizontal scaling, Redis pub/sub, sticky sessions
Patternsreferences/patterns.mdRooms, namespaces, broadcasting, acknowledgments
Securityreferences/security.mdAuthentication, authorization, rate limiting, CORS
Alternativesreferences/alternatives.mdSSE, long polling, when to choose WebSockets

Code Examples

Server Setup (Socket.IO with Auth and Room Management)

js
import { createServer } from "http";
import { Server } from "socket.io";
import { createAdapter } from "@socket.io/redis-adapter";
import { createClient } from "redis";
import jwt from "jsonwebtoken";

const httpServer = createServer();
const io = new Server(httpServer, {
  cors: { origin: process.env.ALLOWED_ORIGIN, credentials: true },
  pingTimeout: 20000,
  pingInterval: 25000,
});

// Authentication middleware — runs before connection is established
io.use((socket, next) => {
  const token = socket.handshake.auth.token;
  if (!token) return next(new Error("Authentication required"));
  try {
    socket.data.user = jwt.verify(token, process.env.JWT_SECRET);
    next();
  } catch {
    next(new Error("Invalid token"));
  }
});

// Redis adapter for horizontal scaling
const pubClient = createClient({ url: process.env.REDIS_URL });
const subClient = pubClient.duplicate();
await Promise.all([pubClient.connect(), subClient.connect()]);
io.adapter(createAdapter(pubClient, subClient));

io.on("connection", (socket) => {
  const { userId } = socket.data.user;
  console.log(`connected: ${userId} (${socket.id})`);

  // Presence: mark user online
  pubClient.hSet("presence", userId, socket.id);

  socket.on("join-room", (roomId) => {
    socket.join(roomId);
    socket.to(roomId).emit("user-joined", { userId });
  });

  socket.on("message", ({ roomId, text }) => {
    io.to(roomId).emit("message", { userId, text, ts: Date.now() });
  });

  socket.on("disconnect", () => {
    pubClient.hDel("presence", userId);
    console.log(`disconnected: ${userId}`);
  });
});

httpServer.listen(3000);

Client-Side Reconnection with Exponential Backoff

js
import { io } from "socket.io-client";

const socket = io("wss://api.example.com", {
  auth: { token: getAuthToken() },
  reconnection: true,
  reconnectionAttempts: 10,
  reconnectionDelay: 1000,       // initial delay (ms)
  reconnectionDelayMax: 30000,   // cap at 30 s
  randomizationFactor: 0.5,      // jitter to avoid thundering herd
});

// Queue messages while disconnected
let messageQueue = [];

socket.on("connect", () => {
  console.log("connected:", socket.id);
  // Flush queued messages
  messageQueue.forEach((msg) => socket.emit("message", msg));
  messageQueue = [];
});

socket.on("disconnect", (reason) => {
  console.warn("disconnected:", reason);
  if (reason === "io server disconnect") socket.connect(); // manual reconnect
});

socket.on("connect_error", (err) => {
  console.error("connection error:", err.message);
});

function sendMessage(roomId, text) {
  const msg = { roomId, text };
  if (socket.connected) {
    socket.emit("message", msg);
  } else {
    messageQueue.push(msg); // buffer until reconnected
  }
}

Constraints

MUST DO

  • Use sticky sessions for load balancing (WebSocket connections are stateful — requests must route to the same server instance)
  • Implement heartbeat/ping-pong to detect dead connections (TCP keepalive alone is insufficient)
  • Use rooms/namespaces for message scoping rather than filtering in application logic
  • Queue messages during disconnection windows to avoid silent data loss
  • Plan connection limits per instance before scaling horizontally

MUST NOT DO

  • Store large state in memory without a clustering strategy (use Redis or an external store)
  • Mix WebSocket and HTTP on the same port without explicit upgrade handling
  • Forget to handle connection cleanup (presence records, room membership, in-flight timers)
  • Skip load testing before production — connection-count spikes behave differently from HTTP traffic spikes

Output Templates

When implementing WebSocket features, provide:

  1. Server setup (Socket.IO/ws configuration)
  2. Event handlers (connection, message, disconnect)
  3. Client library (connection, events, reconnection)
  4. Brief explanation of scaling strategy

Knowledge Reference

Socket.IO, ws, uWebSockets.js, Redis adapter, sticky sessions, nginx WebSocket proxy, JWT over WebSocket, rooms/namespaces, acknowledgments, binary data, compression, heartbeat, backpressure, horizontal pod autoscaling

Documentation

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Websocket Engineer AI skill do?

Use when building real-time communication systems with WebSockets or Socket.IO. Invoke for bidirectional messaging, horizontal scaling with Redis, presence tracking, room management.

Why use Websocket Engineer on TypingMind?

Because you install it once and use it with any model. Websocket Engineer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Websocket Engineer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Jeffallan/claude-skills/tree/main/skills/websocket-engineer. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Websocket Engineer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Websocket Engineer?

As many as you like. As long as a model supports skills, you can use Websocket Engineer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Websocket Engineer AI skill free?

Yes. It is published on GitHub by Jeffallan under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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