BullMQ Specialist workflow skill. Use this skill when the user needs BullMQ expert for Redis-backed job queues, background processing, and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
BullMQ Specialist workflow skill. Use this skill when the user needs BullMQ expert for Redis-backed job queues, background processing, and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
This public intake copy packages plugins/antigravity-awesome-skills-claude/skills/bullmq-specialist from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.
Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.
This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.
BullMQ Specialist BullMQ expert for Redis-backed job queues, background processing, and reliable async execution in Node.js/TypeScript applications.
Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Capabilities, Scope, Tooling, Patterns, Validation Checks, Collaboration.
When to Use This Skill
Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.
User mentions or implies: bullmq
User mentions or implies: bull queue
User mentions or implies: redis queue
User mentions or implies: background job
User mentions or implies: job queue
User mentions or implies: delayed job
Operating Table
Situation
Start here
Why it matters
First-time use
metadata.json
Confirms repository, branch, commit, and imported path through the external_source block before touching the copied workflow
Provenance review
ORIGIN.md
Gives reviewers a plain-language audit trail for the imported source
Workflow execution
SKILL.md
Starts with the smallest copied file that materially changes execution
Supporting context
SKILL.md
Adds the next most relevant copied source file without loading the entire package
Handoff decision
## Related Skills
Helps the operator switch to a stronger native skill when the task drifts
Workflow
This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.
Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
Read the overview and provenance files before loading any copied upstream support files.
Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
Execute the upstream workflow while keeping provenance and source boundaries explicit in the working notes.
Validate the result against the upstream expectations and the evidence you can point to in the copied files.
Escalate or hand off to a related skill when the work moves out of this imported workflow's center of gravity.
Before merge or closure, record what was used, what changed, and what the reviewer still needs to verify.
Imported Workflow Notes
Imported: Capabilities
bullmq-queues
job-scheduling
delayed-jobs
repeatable-jobs
job-priorities
rate-limiting-jobs
job-events
worker-patterns
flow-producers
job-dependencies
Examples
Example 1: Ask for the upstream workflow directly
Use @bullmq-specialist to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.
Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.
Example 2: Ask for a provenance-grounded review
Review @bullmq-specialist against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.
Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.
Example 3: Narrow the copied support files before execution
Use @bullmq-specialist for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.
Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.
Example 4: Build a reviewer packet
Review @bullmq-specialist using the copied upstream files plus provenance, then summarize any gaps before merge.
Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.
Best Practices
Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.
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
Graceful shutdown prevents orphaned jobs - handle SIGTERM properly
Troubleshooting
Problem: The operator skipped the imported context and answered too generically
Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills-claude/skills/bullmq-specialist, fails to mention provenance, or does not use any copied source files at all.
Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.
Problem: The imported workflow feels incomplete during review
Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task.
Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.
Problem: The task drifted into a different specialization
Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better.
Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.
Related Skills
@00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
@00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
@10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
@10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
Additional Resources
Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.
Resource family
What it gives the reviewer
Example path
references
copied reference notes, guides, or background material from upstream
references/n/a
examples
worked examples or reusable prompts copied from upstream
examples/n/a
scripts
upstream helper scripts that change execution or validation
scripts/n/a
agents
routing or delegation notes that are genuinely part of the imported package
agents/n/a
assets
supporting assets or schemas copied from the source package
assets/n/a
Imported Reference Notes
Imported: Scope
redis-infrastructure -> redis-specialist
serverless-queues -> upstash-qstash
workflow-orchestration -> temporal-craftsman
event-sourcing -> event-architect
email-delivery -> email-systems
Imported: 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
Imported: 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,
});
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).
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-systems)
5. Status tracked in Redis (redis-specialist)
Background Processing Stack
Skills: bullmq-specialist, backend, devops
Workflow:
1. API receives request (backend)
2. Long task queued for background (bullmq-specialist)
3. Worker processes async (bullmq-specialist)
4. Result stored/notified (backend)
5. Workers scaled per load (devops)
1. Repeatable jobs defined (bullmq-specialist)
2. Cron patterns with timezone (bullmq-specialist)
3. Jobs execute on schedule (bullmq-specialist)
4. State managed in Redis (redis-specialist)
5. Results handled (backend)
Imported: Limitations
Use this skill only when the task clearly matches the scope described above.
Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
