Amqplib logo

Amqplib

Organization
TerminalSkills
amqplib

You are an expert in amqplib, the Node.js client for RabbitMQ and AMQP 0-9-1 protocol. You help developers implement reliable message queuing with work queues, pub/sub fanout, topic routing, RPC patterns, dead letter queues, and message acknowledgment — building decoupled microservices that communicate asynchronously through RabbitMQ.

Overview

PublisherTerminalSkills
Repositoryskills
Skill nameamqplib
Stars
155
Forks
21
Bundled files
1
LicenseApache-2.0
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Amqplib 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.
  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/TerminalSkills/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/amqplib .claude/skills/amqplib
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Amqplib 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 Amqplib 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 Amqplib 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.

amqplib — RabbitMQ Client for Node.js

You are an expert in amqplib, the Node.js client for RabbitMQ and AMQP 0-9-1 protocol. You help developers implement reliable message queuing with work queues, pub/sub fanout, topic routing, RPC patterns, dead letter queues, and message acknowledgment — building decoupled microservices that communicate asynchronously through RabbitMQ.

Core Capabilities

Producer and Consumer

typescript
import amqp from "amqplib";

// Producer — send messages to queue
async function sendToQueue(queue: string, message: any) {
  const connection = await amqp.connect(process.env.RABBITMQ_URL!);
  const channel = await connection.createChannel();

  await channel.assertQueue(queue, {
    durable: true,                         // Survive broker restart
    arguments: {
      "x-dead-letter-exchange": "dlx",     // Failed messages go to DLX
      "x-message-ttl": 86400000,           // 24h TTL
    },
  });

  channel.sendToQueue(queue, Buffer.from(JSON.stringify(message)), {
    persistent: true,                      // Survive broker restart
    contentType: "application/json",
    messageId: crypto.randomUUID(),
    timestamp: Date.now(),
  });

  await channel.close();
  await connection.close();
}

// Consumer — process messages reliably
async function startConsumer(queue: string, handler: (msg: any) => Promise<void>) {
  const connection = await amqp.connect(process.env.RABBITMQ_URL!);
  const channel = await connection.createChannel();

  await channel.assertQueue(queue, { durable: true });
  await channel.prefetch(10);              // Process 10 at a time

  channel.consume(queue, async (msg) => {
    if (!msg) return;
    try {
      const data = JSON.parse(msg.content.toString());
      await handler(data);
      channel.ack(msg);                    // Success — remove from queue
    } catch (error) {
      console.error("Processing failed:", error);
      channel.nack(msg, false, false);     // Failed — send to DLX (no requeue)
    }
  });
}

// Usage
await sendToQueue("orders", { orderId: "ORD-123", total: 99.99 });
await startConsumer("orders", async (order) => {
  await processOrder(order);
  await sendEmail(order);
});

Pub/Sub with Exchanges

typescript
// Topic exchange — route messages by pattern
async function setupTopicExchange() {
  const connection = await amqp.connect(process.env.RABBITMQ_URL!);
  const channel = await connection.createChannel();

  await channel.assertExchange("events", "topic", { durable: true });

  // Publish events
  channel.publish("events", "order.created", Buffer.from(JSON.stringify({
    orderId: "ORD-456", items: 3,
  })));

  channel.publish("events", "order.shipped", Buffer.from(JSON.stringify({
    orderId: "ORD-456", trackingId: "TRACK-789",
  })));

  channel.publish("events", "user.signup", Buffer.from(JSON.stringify({
    userId: "usr-99", email: "new@user.com",
  })));
}

// Subscribe to patterns
async function subscribeToPattern(pattern: string, handler: (data: any, key: string) => void) {
  const connection = await amqp.connect(process.env.RABBITMQ_URL!);
  const channel = await connection.createChannel();

  await channel.assertExchange("events", "topic", { durable: true });
  const { queue } = await channel.assertQueue("", { exclusive: true });
  await channel.bindQueue(queue, "events", pattern);

  channel.consume(queue, (msg) => {
    if (!msg) return;
    handler(JSON.parse(msg.content.toString()), msg.fields.routingKey);
    channel.ack(msg);
  });
}

// Subscribe to all order events
await subscribeToPattern("order.*", (data, key) => {
  console.log(`Order event [${key}]:`, data);
});

// Subscribe to everything
await subscribeToPattern("#", (data, key) => {
  console.log(`[${key}]:`, data);
});

Installation

bash
npm install amqplib
npm install -D @types/amqplib

# RabbitMQ server
docker run -d -p 5672:5672 -p 15672:15672 rabbitmq:management

Best Practices

  1. Durable queues + persistent messages — Both needed to survive broker restarts; set both always
  2. Manual ack — Never use noAck: true in production; explicitly ack after successful processing
  3. Dead letter exchanges — Configure DLX for failed messages; analyze and retry later
  4. Prefetch — Set channel.prefetch(N) to limit concurrent processing; prevents consumer overload
  5. Connection pooling — Reuse connections, create channels per operation; connections are expensive
  6. Topic exchanges — Use order.* patterns for flexible routing; decouple publishers from consumers
  7. Message TTL — Set x-message-ttl to prevent queue buildup; stale messages expire automatically
  8. Idempotent consumers — Use messageId to deduplicate; messages may be delivered more than once

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 Amqplib AI skill do?

You are an expert in amqplib, the Node.js client for RabbitMQ and AMQP 0-9-1 protocol. You help developers implement reliable message queuing with work queues, pub/sub fanout, topic routing, RPC patterns, dead letter queues, and message acknowledgment — building decoupled microservices that communicate asynchronously through RabbitMQ.

Why use Amqplib on TypingMind?

Because you install it once and use it with any model. Amqplib 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 Amqplib in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/TerminalSkills/skills/tree/main/skills/amqplib. 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 Amqplib?

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 Amqplib?

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

Is the Amqplib AI skill free?

Yes. It is published on GitHub by TerminalSkills under the Apache-2.0 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇