error-handling-patterns

Design cross-language error handling strategies for Python, TypeScript, Rust, and Go.

3|2|Updated Mar 23, 2026
One-click install
npx skills add https://github.com/wesleyegberto/software-engineering-skills --skill error-handling-patterns-wesleyegberto
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: error-handling-patterns
Source: https://github.com/wesleyegberto/software-engineering-skills/tree/main/plugins/programming-skills/skills/error-handling-patterns
Command: npx skills add https://github.com/wesleyegberto/software-engineering-skills --skill error-handling-patterns-wesleyegberto

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Helps teams implement consistent, robust error handling across languages, improving reliability and debuggability.

Core Features & Use Cases

  • Cross-language patterns: exceptions vs Result types, and custom error hierarchies.
  • Language-specific templates and examples for Python, TypeScript, Rust, and Go.
  • Retry, circuit breaker, and graceful degradation patterns; improved observability with clear messages and context.

Quick Start

Apply these patterns to an API endpoint to implement consistent error handling, retries, and graceful degradation.

Frequently Asked Questions about error-handling-patterns

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

FAQPage Schema
How do I implement consistent error handling across Python, TypeScript, Rust, and Go?

To implement consistent error handling across Python, TypeScript, Rust, and Go, you can use cross-language patterns like custom error hierarchies and exceptions versus Result types to ensure predictable errors and clear diagnostics in your distributed components.

When should I use a circuit breaker pattern in API services?

You should use a circuit breaker pattern in API services to enable graceful degradation and prevent cascading failures during distributed component outages. This approach improves system robustness by blocking repeated calls to failing services.

How do I design a retry policy for message queues?

Designing a retry policy for message queues involves implementing structured error propagation patterns with actionable messages. This ensures predictable errors and clear diagnostics during transient failures, maintaining reliable message processing.

What is the difference between using exceptions and Result types for robust error handling?

The difference between exceptions and Result types for robust error handling lies in language-specific paradigms: exceptions use control flow for errors, while Result types explicitly encode error states in return values to ensure predictable error propagation.