Generate Celery task scaffolds with session lifecycle and metrics.
npx skills add https://github.com/michaelayoade/dotmac_crm --skill add-celery-task
Please help me install this Agent Skill. Skill: add-celery-task Source: https://github.com/michaelayoade/dotmac_crm/tree/main/.claude/skills/add-celery-task Command: npx skills add https://github.com/michaelayoade/dotmac_crm --skill add-celery-task
Creating new Celery tasks often leads to inconsistent patterns, circular imports, missing metrics/logging, and brittle error handling that breaks batch processing.
app/tasks/{module}.py destination and whether the task should be scheduled (beat) or run on-demand.SessionLocal() lifecycle management, safe per-item exception handling, logging at start/end, and metrics via observe_job().celery_app.autodiscover_tasks(["app.tasks"]) discovery and documents how to add a beat schedule using scheduler configuration or Celery beat settings.Ask to generate a Celery task for syncing subscribers named "sync_subscribers for Splynx reconciliation" that follows the repository’s existing app/tasks/subscribers.py pattern, includes correct DB session handling and per-item error resilience, and returns processing statistics.
High-intent search queries and answers about installing and using this skill.
Generate Celery background tasks by importing services inside the task function to avoid circular imports, and manage database sessions safely using SessionLocal() for proper lifecycle control.
Add observability and error handling to Python Celery tasks by emitting start and end logs, using observe_job for metrics, and implementing per-item exception handling with database rollback for resilient batch processing.
Set up Celery beat scheduling and autodiscovery by ensuring celery_app.autodiscover_tasks(["app.tasks"]) is configured, then adding periodic background jobs via scheduler configuration or Celery beat settings.
Your Celery batch processing breaks when one item fails due to unhandled exceptions. Prevent this by implementing per-item exception handling with database rollback to isolate failures and allow the batch to continue.
Yes, you can use SQLAlchemy with Celery by applying SessionLocal() lifecycle management, allowing you to build both on-demand and periodic domain tasks that process data safely.
Structure a new Celery task by reading existing task patterns in your repository, placing the module in app/tasks/{module}.py, and applying consistent orchestration rules for logging, metrics, and error handling.
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