result-pattern

Implement SKUEL's Result[T] error handling pattern for service communication.

2|Updated Jan 23, 2026
One-click install
npx skills add https://github.com/linguistic76/skuel --skill result-pattern-linguistic76
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: result-pattern
Source: https://github.com/linguistic76/skuel/tree/main/app/.claude/skills/result-pattern
Command: npx skills add https://github.com/linguistic76/skuel --skill result-pattern-linguistic76

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill provides a comprehensive guide to SKUEL's Result[T] error handling pattern, enabling robust and predictable error management across services.

Core Features & Use Cases

  • Unified Error Handling: Standardizes how errors are represented and propagated internally.
  • Clear Service Contracts: Defines explicit success and failure states for functions.
  • Use Case: When developing a new microservice, use this Skill to implement its error handling strategy, ensuring consistency with the rest of the SKUEL ecosystem and providing clear feedback to clients.

Quick Start

Use the result-pattern skill to understand how to return a validation error from a service function.

Frequently Asked Questions about result-pattern

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

FAQPage Schema
What is the Result type pattern for error handling in Python backend services?

The Result type pattern is a monadic error handling approach that standardizes how errors are represented and propagated internally. It defines explicit success and failure states for service functions, ensuring predictable failure management across microservices.

How do I return a validation error from a service function using a Result type?

To return a validation error from a service function, use the Result pattern's factory methods to categorize the failure by severity level. This creates a clear service contract that propagates the error state to the API boundary for graceful client feedback.

When should I use monadic error handling instead of raising exceptions in API design?

Use monadic error handling in API design when you need unified error categorization and clear service contracts across internal service communication. It replaces unpredictable exceptions with explicit success and failure states, ensuring reliable backend service failures are managed gracefully.

Does the Result pattern work with existing API boundaries in a microservice architecture?

Yes, the Result pattern integrates with API boundaries by translating internal error categorizations and severity levels into appropriate client responses. This integration allows microservices to maintain unified error handling while providing clear feedback to external clients.

How do I categorize error severity levels when implementing a service pattern for internal communication?

Categorize error severity levels by using the factory methods provided by the Result pattern. These methods standardize internal service communication by defining explicit failure states, allowing backend services to differentiate and propagate errors consistently across the ecosystem.

What are the limitations of using a Result type for error handling in Python services?

The Result type requires consistent adoption across services to maintain unified error handling. If internal service communication bypasses the pattern's explicit success and failure states, the clear service contracts degrade, potentially causing unpredictable API boundary behavior.