Error Recovery & Workflow Optimization

关于

This skill transforms error handling from an ad-hoc process into a data-driven engineering discipline by utilizing a taxonomy based on over 1,300 historical errors. It provides Claude with structured diagnostic workflows and recovery patterns—such as exponential backoff and circuit breakers—while introducing automation tools to prevent nearly 24% of common failures. Ideal for complex development sessions where error rates exceed 5% or recovery time is too high, it ensures your AI workflows remain resilient, efficient, and capable of self-correction across any programming language.

主要功能

• 13-category error taxonomy covering 95.4% of common developer failures
• 15 GitHub stars
• Eight specialized diagnostic workflows for file operations, API calls, and resources
• Performance tracking for MTTD (Mean Time To Detect) and error distribution
• Automated prevention tools for file path validation and read-before-write checks
• Five proven recovery patterns including exponential backoff and circuit breakers

使用场景

• Building robust error-handling infrastructure for production-grade projects
• Reducing high error rates in complex automation and long-running sessions
• Performing root cause analysis on recurring or systematic workflow failures