bullmq-specialist
BullMQ expert for Redis-backed job queues, background processing, and reliable async execution in Node.js/TypeScript applications.
What this skill does
# BullMQ Specialist
BullMQ expert for Redis-backed job queues, background processing, and
reliable async execution in Node.js/TypeScript applications.
## Principles
- Jobs are fire-and-forget from the producer side - let the queue handle delivery
- Always set explicit job options - defaults rarely match your use case
- Idempotency is your responsibility - jobs may run more than once
- Backoff strategies prevent thundering herds - exponential beats linear
- Dead letter queues are not optional - failed jobs need a home
- Concurrency limits protect downstream services - start conservative
- Job data should be small - pass IDs, not payloads
- Graceful shutdown prevents orphaned jobs - handle SIGTERM properly
## Capabilities
- bullmq-queues
- job-scheduling
- delayed-jobs
- repeatable-jobs
- job-priorities
- rate-limiting-jobs
- job-events
- worker-patterns
- flow-producers
- job-dependencies
## Scope
- redis-infrastructure -> redis-specialist
- serverless-queues -> upstash-qstash
- workflow-orchestration -> temporal-craftsman
- event-sourcing -> event-architect
- email-delivery -> email-systems
## Tooling
### Core
- bullmq
- ioredis
### Hosting
- upstash
- redis-cloud
- elasticache
- railway
### Monitoring
- bull-board
- arena
- bullmq-pro
### Patterns
- delayed-jobs
- repeatable-jobs
- job-flows
- rate-limiting
- sandboxed-processors
## Patterns
### Basic Queue Setup
Production-ready BullMQ queue with proper configuration
**When to use**: Starting any new queue implementation
import { Queue, Worker, QueueEvents } from 'bullmq';
import IORedis from 'ioredis';
// Shared connection for all queues
const connection = new IORedis(process.env.REDIS_URL, {
maxRetriesPerRequest: null, // Required for BullMQ
enableReadyCheck: false,
});
// Create queue with sensible defaults
const emailQueue = new Queue('emails', {
connection,
defaultJobOptions: {
attempts: 3,
backoff: {
type: 'exponential',
delay: 1000,
},
removeOnComplete: { count: 1000 },
removeOnFail: { count: 5000 },
},
});
// Worker with concurrency limit
const worker = new Worker('emails', async (job) => {
await sendEmail(job.data);
}, {
connection,
concurrency: 5,
limiter: {
max: 100,
duration: 60000, // 100 jobs per minute
},
});
// Handle events
worker.on('failed', (job, err) => {
console.error(`Job ${job?.id} failed:`, err);
});
### Delayed and Scheduled Jobs
Jobs that run at specific times or after delays
**When to use**: Scheduling future tasks, reminders, or timed actions
// Delayed job - runs once after delay
await queue.add('reminder', { userId: 123 }, {
delay: 24 * 60 * 60 * 1000, // 24 hours
});
// Repeatable job - runs on schedule
await queue.add('daily-digest', { type: 'summary' }, {
repeat: {
pattern: '0 9 * * *', // Every day at 9am
tz: 'America/New_York',
},
});
// Remove repeatable job
await queue.removeRepeatable('daily-digest', {
pattern: '0 9 * * *',
tz: 'America/New_York',
});
### Job Flows and Dependencies
Complex multi-step job processing with parent-child relationships
**When to use**: Jobs depend on other jobs completing first
import { FlowProducer } from 'bullmq';
const flowProducer = new FlowProducer({ connection });
// Parent waits for all children to complete
await flowProducer.add({
name: 'process-order',
queueName: 'orders',
data: { orderId: 123 },
children: [
{
name: 'validate-inventory',
queueName: 'inventory',
data: { orderId: 123 },
},
{
name: 'charge-payment',
queueName: 'payments',
data: { orderId: 123 },
},
{
name: 'notify-warehouse',
queueName: 'notifications',
data: { orderId: 123 },
},
],
});
### Graceful Shutdown
Properly close workers without losing jobs
**When to use**: Deploying or restarting workers
const shutdown = async () => {
console.log('Shutting down gracefully...');
// Stop accepting new jobs
await worker.pause();
// Wait for current jobs to finish (with timeout)
await worker.close();
// Close queue connection
await queue.close();
process.exit(0);
};
process.on('SIGTERM', shutdown);
process.on('SIGINT', shutdown);
### Bull Board Dashboard
Visual monitoring for BullMQ queues
**When to use**: Need visibility into queue status and job states
import { createBullBoard } from '@bull-board/api';
import { BullMQAdapter } from '@bull-board/api/bullMQAdapter';
import { ExpressAdapter } from '@bull-board/express';
const serverAdapter = new ExpressAdapter();
serverAdapter.setBasePath('/admin/queues');
createBullBoard({
queues: [
new BullMQAdapter(emailQueue),
new BullMQAdapter(orderQueue),
],
serverAdapter,
});
app.use('/admin/queues', serverAdapter.getRouter());
## Validation Checks
### Redis connection missing maxRetriesPerRequest
Severity: ERROR
BullMQ requires maxRetriesPerRequest null for proper reconnection handling
Message: BullMQ queue/worker created without maxRetriesPerRequest: null on Redis connection. This will cause workers to stop on Redis connection issues.
### No stalled job event handler
Severity: WARNING
Workers should handle stalled events to detect crashed workers
Message: Worker created without 'stalled' event handler. Stalled jobs indicate worker crashes and should be monitored.
### No failed job event handler
Severity: WARNING
Workers should handle failed events for monitoring and alerting
Message: Worker created without 'failed' event handler. Failed jobs should be logged and monitored.
### No graceful shutdown handling
Severity: WARNING
Workers should gracefully shut down on SIGTERM/SIGINT
Message: Worker file without graceful shutdown handling. Jobs may be orphaned on deployment.
### Awaiting queue.add in request handler
Severity: INFO
Queue additions should be fire-and-forget in request handlers
Message: Queue.add awaited in request handler. Consider fire-and-forget for faster response.
### Potentially large data in job payload
Severity: WARNING
Job data should be small - pass IDs not full objects
Message: Job appears to have large inline data. Pass IDs instead of full objects to keep Redis memory low.
### Job without timeout configuration
Severity: INFO
Jobs should have timeouts to prevent infinite execution
Message: Job added without explicit timeout. Consider adding timeout to prevent stuck jobs.
### Retry without backoff strategy
Severity: WARNING
Retries should use exponential backoff to avoid thundering herd
Message: Job has retry attempts but no backoff strategy. Use exponential backoff to prevent thundering herd.
### Repeatable job without explicit timezone
Severity: WARNING
Repeatable jobs should specify timezone to avoid DST issues
Message: Repeatable job without explicit timezone. Will use server local time which can drift with DST.
### Potentially high worker concurrency
Severity: INFO
High concurrency can overwhelm downstream services
Message: Worker concurrency is high. Ensure downstream services can handle this load (DB connections, API rate limits).
## Collaboration
### Delegation Triggers
- redis infrastructure|redis cluster|memory tuning -> redis-specialist (Queue needs Redis infrastructure)
- serverless queue|edge queue|no redis -> upstash-qstash (Need queues without managing Redis)
- complex workflow|saga|compensation|long-running -> temporal-craftsman (Need workflow orchestration beyond simple jobs)
- event sourcing|CQRS|event streaming -> event-architect (Need event-driven architecture)
- deploy|kubernetes|scaling|infrastructure -> devops (Queue needs infrastructure)
- monitor|metrics|alerting|dashboard -> performance-hunter (Queue needs monitoring)
### Email Queue Stack
Skills: bullmq-specialist, email-systems, redis-specialist
Workflow:
```
1. Email request received (API)
2. Job queued with rate limiting (bullmq-specialist)
3. Worker processes with backoff (bullmq-specialist)
4. Email sent via provider (email-systemRelated in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.