dead-letter-queue

Store failed jobs with payload, error, and attempt history for replay.

783|62|Updated Jan 19, 2026

Search Tags:#error handling #resilience #background jobs #dead letter queue #job management #replayability

Ready to run

npx skills add https://github.com/dadbodgeoff/drift --skill dead-letter-queue

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: dead-letter-queue
Source: https://github.com/dadbodgeoff/drift/tree/main/drift%20v1%20depreciated/skills/dead-letter-queue
Command: npx skills add https://github.com/dadbodgeoff/drift --skill dead-letter-queue

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a robust mechanism to capture, store, and manage jobs that fail during processing, preventing data loss and enabling debugging and replay.

Core Features & Use Cases

Capture Failed Jobs: Stores context of failed jobs, including payload, error messages, and attempt history.
Enable Replay: Allows for manual or automated re-processing of failed jobs.
Monitor Failures: Provides statistics on failure patterns, worker-specific issues, and error types.
Use Case: When a critical background job fails after multiple retries, the Dead Letter Queue captures its details so an operator can later inspect the error, fix the underlying issue, and replay the job without losing data.

Quick Start

Use the dead-letter-queue skill to add a failed job with payload, error message, and worker name.

Frequently Asked Questions about dead-letter-queue

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I capture and replay failed background jobs after multiple retries?▼

To capture and replay failed background jobs, you can use a dead letter queue to store the job payload, error messages, and attempt history, enabling manual inspection and automated or manual reprocessing without data loss.

When do I need a dead letter queue for error handling in background job processing?▼

You need a dead letter queue for error handling when a critical background job fails after multiple retries, requiring you to store its context to debug the underlying issue, monitor failure patterns, and safely replay the job later.

How do I add a failed job to a dead letter queue with its payload and error context?▼

To add a failed job to the dead letter queue, you submit the job payload, error message, and worker name, which the system then stores alongside the attempt history for later replay and failure pattern monitoring.

Does this dead letter queue implementation support both Python and TypeScript workers?▼

Yes, the dead letter queue implementation supports both TypeScript and Python, providing worker integration and monitoring capabilities to capture job context and track error attempts across both environments.

How can I monitor failure patterns and worker-specific errors in a dead letter queue?▼

You can monitor failure patterns and worker-specific errors in a dead letter queue by using its built-in statistics features, which track error types and attempt histories to help you identify recurring issues across different workers.