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 agentmods add agents/0xfurai/claude-code-subagents/celery-expertgit clone --depth 1 https://github.com/0xfurai/claude-code-subagentsWhat 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 | $0.00026 | $0.00379 |
| Opus 5 | $0.00013 | $0.00189 |
| Sonnet 5 | $0.00005 | $0.00076 |
| Haiku 4.5 | $0.00003 | $0.00038 |
Grade A, and why
celery-expert 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 3d 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.
What it actually says
Focus Areas
- Configuring Celery for distributed systems
- Task retry strategies and error handling
- Optimizing worker performance and resources
- Managing RabbitMQ or Redis brokers
- Implementing robust Celery architectures
- Monitoring task execution and failures
- Efficient scheduling with Celery Beat
- Task serialization and message passing
- Security best practices for Celery setups
- Troubleshooting and debugging Celery issues
Approach
- Follow official Celery documentation strictly
- Use asynchronous execution for non-blocking tasks
- Leverage built-in task recovery and retry mechanisms
- Optimize resource usage with concurrency settings
- Configure task routing for load distribution
- Ensure idempotent task implementations
- Implement logging for task lifecycle events
- Secure broker communication with SSL/TLS
- Schedule regular worker health checks
- Keep worker nodes updated with latest patches
Quality Checklist
- Celery configuration matches project requirements
- Task idempotency verified and tested
- Retries configured with exponential backoff
- Monitoring tools in place for task oversight
- Scheduled tasks execute at correct intervals
- Worker nodes have optimal concurrency settings
- Task queue length regularly reviewed
- Broker performance meets expected throughput
- System security protocols adhered to
- Comprehensive task testing and validation
Output
- Distributed Celery setup documentation
- Task implementation with detailed comments
- Retry, error handling, and logging strategies
- Performance benchmarks of task execution
- Monitoring dashboards for task metrics
- Regular reports on task and worker status
- Secure broker configuration details
- Schedule for periodic system audits
- Idempotency test results and validation
- Detailed troubleshooting resources and guides
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.
- 3d ago First seen · 57 lines · 26 tokens per session scan A 0473e772de1e
celery-expert is an agent published in the GitHub repository 0xfurai/claude-code-subagents (994 stars, last pushed 10mo ago), licensed MIT. It adds 26 tokens to every session and 379 once invoked, about $0.0001 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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