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.
git clone --depth 1 https://github.com/TechNickAI/claude_telemetryWrote 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/rules/technickai/claude_telemetry/celery-task-structure)<a href="https://agentmods.dev/rules/technickai/claude_telemetry/celery-task-structure"><img src="https://agentmods.dev/badge/rules/technickai/claude_telemetry/celery-task-structure/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/rules/technickai/claude_telemetry/celery-task-structure"><img src="https://agentmods.dev/badge/rules/technickai/claude_telemetry/celery-task-structure.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00000 | $0.00572 |
| Opus 5.5 | $0.00000 | $0.00229 |
| Sonnet 5.5 | $0.00000 | $0.00114 |
| Haiku 4.5 | $0.00000 | $0.00057 |
Grade A, and why
celery-task-structure 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- celery-task-structure — 100% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Celery Task Structure
Task Definition
@shared_task(max_retries=3, default_retry_delay=60)
def process_order(order_id: int):
"""Process order and send confirmation email."""
logger.info(f"Processing order {order_id}")
order = Order.objects.get(id=order_id)
order.process_payment()
send_confirmation_email(order)
logger.info(f"Order {order_id} complete")
return {"status": "success", "order_id": order_id}
@shared_task(rate_limit="10/m")
def sync_inventory(product_id: int):
"""Sync product inventory from external API."""
product = Product.objects.get(id=product_id)
inventory_data = fetch_inventory_from_api(product.sku)
product.stock_count = inventory_data["quantity"]
product.save()
return {"product_id": product_id, "stock": product.stock_count}
@shared_task
def generate_daily_report(date: str):
"""Generate and email daily sales report."""
report_date = datetime.fromisoformat(date)
report = compile_sales_report(report_date)
send_report_email(report)
return {"date": date, "orders": report.order_count}
Best Practices
We:
- Use type hints for parameters
- Include helpful docstrings
- Log start and completion
- Set appropriate retry settings
- Consider rate limits for external APIs
- Pass IDs, not objects (objects can't be serialized)
- Return serializable data (dicts, not model instances)
Error Handling
Default: let exceptions bubble up. Celery will retry based on max_retries setting.
For specific retry behavior:
@shared_task(max_retries=3, default_retry_delay=60)
def sync_external_data(data_id: int):
"""Sync data from external API with retry on transient failures."""
data = Data.objects.get(id=data_id) # Let it crash if data doesn't exist
try:
result = external_api_call(data)
return result
except ExternalAPIError as exc:
# Retry on transient API errors
raise self.retry(exc=exc)
Honeybadger/Sentry will alert us on failures. Let tasks crash on real problems.
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.
- 1mo ago First seen · 88 lines · 572 tokens per session scan A 0324aedc91c6
celery-task-structure is a cursor rule published in the GitHub repository TechNickAI/claude_telemetry (31 stars, last pushed 11mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 572 tokens. 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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