agents-inc/skills

BullMQ Patterns

Quick Guide: Use BullMQ (v5.x) for background job processing, task scheduling, and workflow orchestration on top of Redis. Core classes: Queue (adds jobs), Worker (processes jobs), QueueEvents (global event listener), FlowProducer (parent-child job trees). Always pass a connection object to every constructor (required in v5). Set maxRetriesPerRequest: null on ioredis connections for Workers. Use upsertJobScheduler for repeatable/cron jobs (replaces deprecated repeatable API). QueueScheduler was removed in v4 -- its responsibilities are now handled by Workers automatically.

---

<critical_requirements>

CRITICAL: Before Using This Skill

All code must follow project conventions in CLAUDE.md (kebab-case, named exports, import ordering, import type, named constants)

(You MUST pass a connection object to every Queue, Worker, QueueEvents, and FlowProducer constructor -- BullMQ v5 throws if connection is missing)

(You MUST set maxRetriesPerRequest: null on ioredis connections used by Workers -- BullMQ requires infinite retries and throws without this setting)

(You MUST call await worker.close() on SIGTERM/SIGINT for graceful shutdown -- without it, in-progress jobs become stalled)

(You MUST use upsertJobScheduler for repeatable/cron jobs -- the old repeat option on queue.add is deprecated since v5.16.0)

</critical_requirements>

---

Examples

• Core Patterns -- Queue setup, Worker processing, job options, connection factory, graceful shutdown, typed jobs
• Advanced Patterns -- FlowProducer, rate limiting, job scheduling, QueueEvents, concurrency, sandboxed processors

Additional resources:

• reference.md -- Decision frameworks, job option reference, anti-patterns, production checklist

---

Auto-detection: BullMQ, bullmq, Queue, Worker, QueueEvents, FlowProducer, job queue, background job, worker process, job scheduler, upsertJobScheduler, rate limiter, job priority, job delay, sandboxed processor, repeatable job, cron job, flow producer, parent child jobs

When to use:

• Background processing (email sending, image processing, PDF generation)
• Scheduled/cron jobs (nightly reports, periodic cleanup)
• Workflow orchestration with parent-child job dependencies (FlowProducer)
• Rate-limited API consumption (throttling outbound requests)
• Priority-based job processing (urgent jobs before bulk operations)
• Distributing CPU-intensive work across multiple workers or machines

Key patterns covered:

• Queue and Worker setup with typed job data and return values
• Connection factory with maxRetriesPerRequest: null for Workers
• Job options: delay, priority, attempts, backoff, removeOnComplete/Fail
• Graceful shutdown with worker.close() on process signals
• FlowProducer for parent-child job trees with dependency tracking
• Job Schedulers for repeatable/cron jobs (upsertJobScheduler)
• Rate limiting (global limiter and manual Worker.RateLimitError)
• Concurrency control (local per-worker and global)
• QueueEvents for global event monitoring across all workers
• Sandboxed processors for CPU-intensive work

When NOT to use:

• Simple in-process timers or setTimeout (no persistence needed)
• Real-time pub/sub messaging without persistence (use your pub/sub solution)
• Data that must be processed synchronously within a request-response cycle
• Queues that don't need persistence, retries, or scheduling

---

Philosophy

BullMQ is a Redis-backed job queue for Node.js that provides reliable background processing with at-least-once delivery guarantees. The core principle: separate job production from job consumption so your application stays responsive while work happens asynchronously.

Core principles:

1. Producers and consumers are decoupled -- Any process can add jobs to a queue; any Worker can process them. This enables horizontal scaling by adding more Workers.
2. Jobs are persistent -- Jobs survive process restarts because they live in Redis. A crashed Worker's jobs are picked up by other Workers (or the same Worker after restart).
3. At-least-once delivery -- BullMQ guarantees every job is processed at least once. Use idempotent processors to handle the (rare) case of duplicate processing after a stall.
4. Fail gracefully with retries -- Configure attempts and backoff strategies so transient failures resolve automatically. Permanently failed jobs move to the failed set for inspection.
5. Each Queue/Worker/QueueEvents needs its own connection -- BullMQ manages connection state internally. Never share a single ioredis instance across multiple BullMQ classes (except Queues acting only as producers).

---

Core Patterns

Pattern 1: Connection Factory

BullMQ v5 requires an explicit Redis connection on every constructor. Workers need maxRetriesPerRequest: null so ioredis retries indefinitely instead of giving up.

import Redis from "ioredis";

function createBullMQConnection(): Redis {
  const url = process.env.REDIS_URL;
  if (!url) throw new Error("REDIS_URL is required");
  return new Redis(url, { maxRetriesPerRequest: null });
}
export { createBullMQConnection };

Why good: maxRetriesPerRequest: null satisfies BullMQ's requirement, factory ensures consistent config, environment variable keeps credentials out of code

// Bad -- missing maxRetriesPerRequest
const redis = new Redis("redis://localhost:6379");
const worker = new Worker("emails", processor, { connection: redis });
// BullMQ throws: "maxRetriesPerRequest must be null"

Why bad: BullMQ requires infinite retries on Worker connections and will throw at startup without null

See examples/core.md for the full connection factory with producer vs consumer separation.

---

Pattern 2: Queue and Worker Setup

Queue adds jobs; Worker processes them. Both accept TypeScript generics for type-safe job data and return values.

import { Queue, Worker, type Job } from "bullmq";

interface EmailJobData {
  to: string;
  subject: string;
  body: string;
}

const QUEUE_NAME = "emails";

const emailQueue = new Queue<EmailJobData>(QUEUE_NAME, {
  connection: createBullMQConnection(),
});

const emailWorker = new Worker<EmailJobData>(
  QUEUE_NAME,
  async (job: Job<EmailJobData>) => {
    await sendEmail(job.data.to, job.data.subject, job.data.body);
  },
  { connection: createBullMQConnection() },
);

Why good: Generics enforce type safety on job.data, separate connections for Queue and Worker, named constant for queue name

See examples/core.md for full setup with events, error handling, and typed return values.

---

Pattern 3: Job Options

Control job behavior with options: delay, priority, retries, backoff, and auto-removal.

const MAX_ATTEMPTS = 5;
const BACKOFF_DELAY_MS = 1000;
const DELAY_MS = 60_000;
const KEEP_COMPLETED_COUNT = 100;

await emailQueue.add(
  "send-welcome",
  { to: "[email protected]", subject: "Welcome", body: "..." },
  {
    delay: DELAY_MS,
    priority: 1, // 1 = highest, higher numbers = lower priority
    attempts: MAX_ATTEMPTS,
    backoff: { type: "exponential", delay: BACKOFF_DELAY_MS },
    removeOnComplete: { count: KEEP_COMPLETED_COUNT },
    removeOnFail: false,
  },
);

Why good: Named constants for all numeric values, exponential backoff for transient failures, removeOnComplete with count prevents unbounded Redis memory, removeOnFail: false preserves failed jobs for debugging

See examples/core.md for defaultJobOptions, addBulk, and LIFO patterns.

---

Pattern 4: Graceful Shutdown

Call worker.close() on process signals to finish in-progress jobs before exiting. Without this, jobs become stalled and are re-processed by other Workers.

async function shutdown(workers: Worker[]): Promise<void> {
  await Promise.all(workers.map((w) => w.close()));
  process.exit(0);
}

process.on("SIGTERM", () => shutdown([emailWorker]));
process.on("SIGINT", () => shutdown([emailWorker]));

Why good: close() stops accepting new jobs and waits for in-progress jobs to finish, Promise.all handles multiple workers, signal handlers cover both SIGTERM and SIGINT

Gotcha: worker.close() has no built-in timeout. If a processor hangs, the shutdown hangs. Wrap with your own timeout if needed.

See examples/core.md for shutdown with timeout pattern.

---

Pattern 5: FlowProducer (Parent-Child Jobs)

FlowProducer creates job trees where parent jobs wait for all children to complete. The entire tree is added atomically.

import { FlowProducer } from "bullmq";

const flowProducer = new FlowProducer({ connection: createBullMQConnection() });

await flowProducer.add({
  name: "publish-video",
  queueName: "videos",
  children: [
    { name: "extract-audio", queueName: "media", data: { videoId: "abc" } },
    {
      name: "generate-thumbnail",
      queueName: "media",
      data: { videoId: "abc" },
    },
    {
      name: "transcode",
      queueName: "media",
      data: { videoId: "abc", format: "mp4" },
    },
  ],
});

Why good: Parent waits until all children complete, atomic addition (all or nothing), children can be in different queues, parent processor can access children results via job.getChildrenValues()

See examples/advanced.md for accessing children values and nested flows.

---

Pattern 6: Job Schedulers (Repeatable/Cron Jobs)

Use upsertJobScheduler (v5.16.0+) for repeatable jobs. Replaces the deprecated repeat option.

const REPORT_INTERVAL_MS = 3_600_000; // 1 hour

// Fixed interval
await emailQueue.upsertJobScheduler(
  "hourly-digest",
  { every: REPORT_INTERVAL_MS },
  {
    name: "send-digest",
    data: { type: "hourly" },
  },
);

// Cron expression -- daily at 3:15 AM
await emailQueue.upsertJobScheduler(
  "nightly-cleanup",
  { pattern: "0 15 3 * * *" },
  {
    name: "cleanup",
    data: { type: "nightly" },
    opts: { removeOnComplete: true },
  },
);

Why good: upsertJobScheduler is idempotent (safe to call on every startup), template defines job name/data/opts inherited by each produced job, cron syntax via pattern

Gotcha: every intervals align to the clock, not to when you called upsertJobScheduler. A 2000ms interval fires at 0s, 2s, 4s, etc.

See examples/advanced.md for removing schedulers and listing active schedulers.

---

Pattern 7: Rate Limiting

Limit how many jobs a Worker processes per time window. The limiter is global across all Workers on the same queue.

const RATE_LIMIT_MAX = 10;
const RATE_LIMIT_DURATION_MS = 1000;

const worker = new Worker("api-calls", processor, {
  connection: createBullMQConnection(),
  limiter: { max: RATE_LIMIT_MAX, duration: RATE_LIMIT_DURATION_MS },
});

Why good: Global rate limit (10 workers with this config still process max 10 jobs/second total), named constants for limits

For dynamic rate limiting based on external API responses, use worker.rateLimit(duration) + throw Worker.RateLimitError(). See examples/advanced.md.

---

Pattern 8: QueueEvents for Global Monitoring

QueueEvents uses Redis Streams (not Pub/Sub) so events are reliable even across reconnections. Requires its own dedicated connection.

import { QueueEvents } from "bullmq";

const queueEvents = new QueueEvents(QUEUE_NAME, {
  connection: createBullMQConnection(),
});

queueEvents.on("completed", ({ jobId, returnvalue }) => {
  console.log(`Job ${jobId} completed with: ${returnvalue}`);
});

queueEvents.on("failed", ({ jobId, failedReason }) => {
  console.error(`Job ${jobId} failed: ${failedReason}`);
});

Why good: Monitors all Workers on a queue from a single listener, reliable delivery via Redis Streams, separate connection as required

See examples/advanced.md for progress tracking and waiting for specific job completion.

---

Performance Optimization

• Concurrency -- Set concurrency on Worker options to process multiple jobs in parallel within a single Worker instance: { concurrency: 10 }. Only effective for I/O-bound work. CPU-bound work blocks the event loop and causes stalled jobs -- use sandboxed processors instead.
• Sandboxed processors -- Pass a file path instead of a function to the Worker constructor to run processors in a separate process (or worker thread with useWorkerThreads: true). Prevents CPU-intensive work from blocking lock renewal.
• addBulk -- Use queue.addBulk([...]) to add many jobs in a single Redis round-trip instead of calling queue.add() in a loop.
• removeOnComplete/Fail -- Configure auto-removal to prevent unbounded Redis memory growth. Use { count: N } to keep the last N jobs for debugging.
• Separate connections -- Producers (Queue) can share a connection. Workers and QueueEvents each need their own connection due to blocking Redis commands.

---

<decision_framework>

Decision Framework

When to Use BullMQ

Do you need background job processing?
|-- NO -> Don't use BullMQ
+-- YES -> Do you need persistence, retries, or scheduling?
    |-- NO -> Simple in-process queue or setTimeout may suffice
    +-- YES -> Do you need parent-child job dependencies?
        |-- YES -> BullMQ with FlowProducer
        +-- NO -> Do you need rate limiting or priority?
            |-- YES -> BullMQ with limiter/priority options
            +-- NO -> BullMQ with basic Queue + Worker

Which Job Pattern?

What kind of job scheduling do you need?
|-- One-time delayed job -> queue.add() with delay option
|-- Recurring on fixed interval -> upsertJobScheduler with every
|-- Recurring on cron schedule -> upsertJobScheduler with pattern
|-- Job that depends on other jobs -> FlowProducer with children
|-- Bulk of independent jobs -> queue.addBulk([...])

Concurrency Strategy

Is the processor CPU-intensive?
|-- YES -> Use sandboxed processor (file path or useWorkerThreads)
+-- NO -> Is it I/O-bound (network calls, DB queries)?
    |-- YES -> Set concurrency option (e.g., 10-50)
    +-- NO -> Default concurrency (1) is fine

</decision_framework>

---

<red_flags>

RED FLAGS

High Priority Issues:

• Missing connection on Queue/Worker/QueueEvents constructor -- BullMQ v5 throws at startup without it
• Missing maxRetriesPerRequest: null on Worker connections -- BullMQ throws immediately
• No graceful shutdown handler -- in-progress jobs become stalled on process exit and are re-processed by other Workers
• Using deprecated repeat option on queue.add() instead of upsertJobScheduler -- deprecated since v5.16.0
• Using integer job IDs -- BullMQ v5 throws; IDs must be strings

Medium Priority Issues:

• No removeOnComplete/removeOnFail configured -- completed/failed jobs accumulate in Redis indefinitely
• Sharing a single ioredis connection between Worker and QueueEvents -- both use blocking commands and will interfere
• CPU-intensive processor without sandboxed mode -- blocks event loop, causes stalled jobs, prevents lock renewal
• Missing error event handler on Worker -- worker.on("error", ...) prevents unhandled errors from crashing the process

Common Mistakes:

• Assuming worker.close() has a timeout -- it waits indefinitely for processors to finish; wrap with your own timeout
• Using QueueScheduler class -- removed in BullMQ v4; its responsibilities are handled by Workers automatically
• Expecting limiter to be per-Worker -- the rate limit is global across all Workers on the same queue
• Not making processors idempotent -- BullMQ guarantees at-least-once delivery; a stalled job may be processed twice

Gotchas & Edge Cases:

• upsertJobScheduler every intervals align to the clock (0s, 2s, 4s), not to when you called the method
• worker.close() does not cancel running processors -- it waits for them to finish naturally
• Job priority has a performance cost -- BullMQ uses a different data structure for priority queues; skip if not needed
• QueueEvents uses Redis Streams internally -- ensure your Redis instance has sufficient memory for stream data
• FlowProducer adds the entire tree atomically -- if any child fails validation, none are added
• job.getChildrenValues() returns an object keyed by "queueName:jobId" -- not an array
• Redis must have maxmemory-policy set to noeviction -- BullMQ relies on keys not being evicted

</red_flags>

---

<critical_reminders>

CRITICAL REMINDERS

All code must follow project conventions in CLAUDE.md (kebab-case, named exports, import ordering, import type, named constants)

(You MUST pass a connection object to every Queue, Worker, QueueEvents, and FlowProducer constructor -- BullMQ v5 throws if connection is missing)

(You MUST set maxRetriesPerRequest: null on ioredis connections used by Workers -- BullMQ requires infinite retries and throws without this setting)

(You MUST call await worker.close() on SIGTERM/SIGINT for graceful shutdown -- without it, in-progress jobs become stalled)

(You MUST use upsertJobScheduler for repeatable/cron jobs -- the old repeat option on queue.add is deprecated since v5.16.0)

Failure to follow these rules will cause startup crashes, stalled jobs, and unreliable job processing.

</critical_reminders>