error-coordinator

Name: error-coordinator
Availability: InStock
Author: belokonm

Coordinate error handling and self-healing workflows for multi-agent systems.

8|11|Updated Feb 15, 2026

Search Tags:#multi-agent #robustness #reliability #error-handling #self-healing #circuit-breaker #failure-recovery

Ready to run

npx skills add https://github.com/belokonm/claude-supercode-skills --skill error-coordinator-belokonm

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: error-coordinator
Source: https://github.com/belokonm/claude-supercode-skills/tree/main/error-coordinator-skill
Command: npx skills add https://github.com/belokonm/claude-supercode-skills --skill error-coordinator-belokonm

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Provides expert guidance and frameworks for building resilient, self-healing multi-agent systems with robust error handling, loop detection, and recovery workflows.

Core Features & Use Cases

Loop detection and escape-hatch triggers to prevent infinite agent recursion.
Hallucination mitigation by grounding outputs with context and validation.
Circuit breaker patterns and coordinated failure recovery across agents.
Self-healing workflows and retry orchestration to maintain system reliability.

Quick Start

Design and implement a resilient, self-healing multi-agent workflow by configuring error handling, retry strategies, and agent coordination.

Frequently Asked Questions about error-coordinator

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

FAQPage Schema

How do I prevent infinite loops in multi-agent systems?▼

Prevent infinite agent recursion in multi-agent systems by implementing loop detection and escape-hatch triggers. This stops cycles before they degrade workflow reliability and ensures agents terminate gracefully.

How does a circuit breaker pattern work for distributed AI agents?▼

A circuit breaker pattern for distributed AI agents monitors for failure thresholds and temporarily halts requests to a failing component. This coordinated failure recovery prevents cascading errors across your multi-agent workflow.

What is the best way to add self-healing workflows to production AI agents?▼

Add self-healing workflows to production AI agents by configuring retry orchestration with backoff logic. This maintains system reliability by automatically re-attempting failed operations and coordinating recovery across distributed agents.

How do I mitigate hallucination in distributed agent outputs?▼

Mitigate hallucination in distributed agent outputs by grounding responses with context and validation rules. This technique constrains the agent's output to verified data and reduces ungrounded speculation in multi-agent systems.

Do I need predefined decision rules for multi-agent failure recovery?▼

Yes, multi-agent failure recovery requires clear predefined decision rules to coordinate actions correctly. Explicit rules govern backoff, retry logic, and circuit-breaker triggers to ensure robust and predictable self-healing.