python-resilience
Python Resilience Patterns
Build fault-tolerant Python applications that gracefully handle transient failures, network issues, and service outages. Resilience patterns keep systems running when dependencies are unreliable.
When to Use This Skill
- Adding retry logic to external service calls
- Implementing timeouts for network operations
- Building fault-tolerant microservices
- Handling rate limiting and backpressure
- Creating infrastructure decorators
- Designing circuit breakers
Core Concepts
1. Transient vs Permanent Failures
Retry transient errors (network timeouts, temporary service issues). Don't retry permanent errors (invalid credentials, bad requests).
More from ericgrill/agents-skills-plugins
debugging-strategies
Master systematic debugging techniques, profiling tools, and root cause analysis to efficiently track down bugs across any codebase or technology stack. Use when investigating bugs, performance issues, or unexpected behavior.
10test-driven-development
Use when implementing any feature or bugfix, before writing implementation code
9subagent-driven-development
Use when executing implementation plans with independent tasks in the current session
9systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
9nodejs-backend-patterns
Build production-ready Node.js backend services with Express/Fastify, implementing middleware patterns, error handling, authentication, database integration, and API design best practices. Use when creating Node.js servers, REST APIs, GraphQL backends, or microservices architectures.
9openapi-spec-generation
Generate and maintain OpenAPI 3.1 specifications from code, design-first specs, and validation patterns. Use when creating API documentation, generating SDKs, or ensuring API contract compliance.
8