error-recovery

Standardize retry, fallback, and escalation strategies for autonomous agent workflows.

1|Updated Dec 23, 2025

Search Tags:#automation #resilience #reliability #best-practices #error-handling #agent-coordination

Ready to run

npx skills add https://github.com/jonnymuir/Umbraco.Prism --skill error-recovery-jonnymuir

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: error-recovery
Source: https://github.com/jonnymuir/Umbraco.Prism/tree/main/.copilot/skills/error-recovery
Command: npx skills add https://github.com/jonnymuir/Umbraco.Prism --skill error-recovery-jonnymuir

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill addresses the lack of consistency in how AI agents handle failures, preventing them from simply reporting errors and instead guiding them to adapt and recover autonomously.

Core Features & Use Cases

Structured Recovery Patterns: Provides five proven strategies including Retry with Backoff, Fallback Alternatives, and Graceful Degradation.
Escalation Protocols: Defines clear boundaries for when an agent should stop attempting recovery and hand off to a human or coordinator.
Use Case: When an API call fails due to rate limiting, the agent uses the Retry with Backoff pattern to wait and retry, rather than immediately failing the entire task.

Quick Start

Apply the error-recovery patterns to your current agent charter to ensure robust handling of transient network failures and build errors.

Frequently Asked Questions about error-recovery

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

FAQPage Schema

How do I handle API rate limiting errors in autonomous agent workflows?▼

To handle API rate limiting in autonomous agent workflows, apply a Retry with Backoff pattern. This strategy directs the agent to wait and retry the failed network request autonomously, maintaining operational continuity instead of immediately failing the entire task.

What are the best strategies for error recovery and resilience in distributed systems?▼

Error recovery and resilience in distributed systems utilize five structured patterns, including Retry with Backoff, Fallback Alternatives, and Graceful Degradation. These standardized strategies ensure high reliability during transient network failures.

When should an autonomous agent escalate a failure instead of retrying?▼

An autonomous agent should escalate a failure when it hits predefined boundaries for recovery attempts. Escalation protocols define exactly when the agent must stop retrying transient errors and hand off the workflow to a human or coordinator.

How do I standardize error handling across automated build pipelines?▼

To standardize error handling across automated build pipelines, apply structured resilience patterns to your agent charter. This implements deterministic retry, fallback, and escalation strategies to maintain operational continuity during transient failures.

Does this error-handling approach work without external dependencies?▼

Yes, this error-handling approach works without external dependencies. The resilience patterns apply directly to your agent charter logic, requiring no additional modules to implement fallback alternatives or escalation protocols for API integrations.