error-recovery-patterns

# Error Recovery Patterns Skill Use this skill for error handling, recovery strategies, and debugging in gh-aw. ## Purpose Implement robust recovery patterns to: - Reduce retry loops in agent sessions (target: <10% vs current 23%) - Implement circuit breakers to prevent infinite retry loops - Add proactive recovery for installation, dependency, and API failures - Improve debug logging for recovery attempts ## When to Use This Skill Use this skill when: - Implementing retry logic for network operations, installations, or API calls - Debugging retry loop issues in workflows or agent sessions - Adding error recovery patterns to new or existing code - Understanding transient vs non-transient error classification - Implementing circuit breakers or exponential backoff - Adding debug logging for recovery attempts ## Key Concepts Covered ### 1. Circuit Breaker Pattern - Maximum retry limits (standard: 3 attempts) - Exponential backoff strategies - Fail-fast on non-transient errors - Implementation in JavaScript, Shell, and Go ### 2. Installation Failure Recovery - NPM installation with cache clearing and registry fallbacks - Python pip installation with mirror alternatives - Docker image pull with retry and rate limit handling - Copilot CLI installation with network retry ### 3. API Timeout and Rate Limit Handling - GitHub API rate limit detection and backoff - Transient error detection patterns - Custom retry configuration for different APIs - Rate limit-specific retry stra...