from ai-workspace-archive12
Production-grade Django + Celery patterns: setup, task design, beat scheduling, retries, canvas workflows, testing, and monitoring for background jobs.
This skill collects production-ready patterns and examples for integrating Celery into Django projects. It covers setup (broker/backends), app entrypoints, task design (idempotency, retries, soft/hard time limits), scheduling with Celery Beat (code and database-driven), chaining/grouping (chain/group/chord), testing strategies, and operational monitoring (Flower, inspect, Redis checks).
Activate when adding background processing to a Django app: sending emails, generating PDFs, syncing to external systems, scheduling periodic jobs, or when you need guidance on retries, dead-letter handling, and monitoring task health. Useful during development and production hardening.
Useful for agents that generate or modify project code (Copilot-style, Codex, or developer-focused assistants) and for ops agents that can run CLI commands to manage workers and monitors.
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Claimable Postgres (pg.new)
Provision instant temporary Postgres databases via Neon's Claimable Postgres (pg.new) for quick development, demos, and prototypes without signup; returns a DAT
Obsidian CLI Reference
Reference and usage guide for the Obsidian CLI: read, create, search, and manage notes, plus developer commands for plugin/theme development and debugging.
Git Hooks Automation
Set up and manage Git hooks (Husky, lint-staged, pre-commit) to enforce linting, formatting, tests, and commit message rules before code reaches CI.
Segment CDP
Patterns and best practices for integrating Segment (Analytics.js and server SDK) to capture client- and server-side events, design tracking plans, and avoid co
Homelab Pihole Dns
Pi-hole installation, blocklist management, DNS-over-HTTPS setup, DHCP integration, local DNS records, and troubleshooting broken DNS resolution on a home ne...
