When should I use Oban Pro Workflows vs. simple job chaining?

Simple linear chains should use basic job enqueuing for less overhead. Use Workflows for complex dependency graphs, fan-out/fan-in patterns, or when you need to record and pass values across multiple steps.

How do I test Oban workflows effectively?

This skill recommends using run_workflow/1 for integration tests rather than inline testing mode, as workflows require actual database interaction to properly test dependencies and recorded values.

Should I use try/rescue inside an Oban perform/1 function?

Generally, no. Oban follows the 'let it crash' philosophy to handle retries and logging automatically. This skill guides you on when to catch errors for custom logic and when to let them bubble up for Oban to handle.

Why do my Oban job arguments change from atoms to strings?

Oban job arguments are serialized to JSON in the database, which converts Elixir atoms into strings. This skill helps you implement the correct string-based pattern-matching logic in your perform functions.

Oban Job Processing Optimizer

Name: Oban Job Processing Optimizer
Author: ahmedxx99

byahmedxx99

API Development

Provides expert guidance and implementation patterns for robust background job processing using Oban and Oban Pro in Elixir.

About

This skill equips Claude with specialized knowledge for architecting, implementing, and troubleshooting background jobs in Elixir using the Oban library. It covers critical patterns such as JSON serialization safety, 'let-it-crash' error handling, and complex workflow orchestration using Oban Pro features like cascading context and grafting. By applying these insights, developers can prevent common serialization bugs, optimize high-throughput processing with batching, and build resilient asynchronous systems that leverage the full power of PostgreSQL-backed job queues.

Key Features

0 GitHub stars
Provides debugging strategies for job failures, uniqueness constraints, and testing
Implements 'let-it-crash' error handling for automatic retries and visibility
Guides complex workflow orchestration using Oban Pro Graft and Cascade patterns
Enforces JSON serialization best practices to prevent atom/string mismatch bugs
Optimizes high-throughput processing via efficient database-friendly chunking

Use Cases

Designing multi-step data processing pipelines with complex dependencies
Scaling background tasks to handle millions of records without database strain
Troubleshooting silent job failures and serialization errors in production

About

Key Features

0 GitHub stars
Provides debugging strategies for job failures, uniqueness constraints, and testing
Implements 'let-it-crash' error handling for automatic retries and visibility
Guides complex workflow orchestration using Oban Pro Graft and Cascade patterns
Enforces JSON serialization best practices to prevent atom/string mismatch bugs
Optimizes high-throughput processing via efficient database-friendly chunking

Use Cases

Designing multi-step data processing pipelines with complex dependencies
Scaling background tasks to handle millions of records without database strain
Troubleshooting silent job failures and serialization errors in production