Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add curiositech/some_claude_skills --skill background-job-orchestratorgit clone --depth 1 https://github.com/curiositech/some_claude_skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/curiositech/some_claude_skills/background-job-orchestrator)<a href="https://agentmods.dev/skills/curiositech/some_claude_skills/background-job-orchestrator"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/background-job-orchestrator/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/curiositech/some_claude_skills/background-job-orchestrator"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/background-job-orchestrator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00095 | $0.03216 |
| Opus 5 | $0.00048 | $0.01608 |
| Sonnet 5 | $0.00019 | $0.00643 |
| Haiku 4.5 | $0.00010 | $0.00322 |
Grade A, and why
background-job-orchestrator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 508 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Background Job Orchestrator
Expert in designing and implementing production-grade background job systems that handle long-running tasks without blocking API responses.
When to Use
✅ Use for:
- Long-running tasks (email sends, report generation, image processing)
- Batch operations (bulk imports, exports, data migrations)
- Scheduled tasks (daily digests, cleanup jobs, recurring reports)
- Tasks requiring retry logic (external API calls, flaky operations)
- Priority-based processing (premium users first, critical alerts)
- Rate-limited operations (API quotas, third-party service limits)
❌ NOT for:
- Real-time bidirectional communication (use WebSockets)
- Sub-second latency requirements (use in-memory caching)
- Simple delays (setTimeout is fine for <5 seconds)
- Synchronous API responses (keep logic in request handler)
Quick Decision Tree
Does this task:
├── Take >5 seconds? → Background job
├── Need to retry on failure? → Background job
├── Run on a schedule? → Background job (cron pattern)
├── Block user interaction? → Background job
├── Process in batches? → Background job
└── Return immediately? → Keep synchronous
Technology Selection
Node.js: BullMQ (Recommended 2024+)
When to use:
- TypeScript project
- Redis already in stack
- Need advanced features (rate limiting, priorities, repeatable jobs)
Why BullMQ over Bull:
- Bull (v3) → BullMQ (v4+): Complete rewrite in TypeScript
- Better Redis connection handling
- Improved concurrency and performance
- Active maintenance (Bull is in maintenance mode)
Python: Celery
When to use:
- Python/Django project
- Need distributed task execution
- Complex workflows (chains, groups, chords)
Alternatives:
- RQ (Redis Queue): Simpler, fewer features
- Dramatiq: Modern, less ecosystem
- Huey: Lightweight, good for small projects
Cloud-Native: AWS SQS, Google Cloud Tasks
When to use:
- Serverless architecture
- Don't want to manage Redis/RabbitMQ
- Need guaranteed delivery and dead-letter queues
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 508 lines · 95 tokens per session scan A 7e6d6ce15700
background-job-orchestrator is a skill published in the GitHub repository curiositech/some_claude_skills (221 stars, last pushed 5d ago), licensed MIT. It adds 95 tokens to every session and 3,216 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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