skills.rest
PixnBits
PixnBitsCOMMUNITY
Explore all skills by this author →
Website𝕏@pixnbitsGitHub

RetryOrchestratorSkill

Monitor message bus events and emit recovery directives for AI agent swarms.

Updated Feb 25, 2026
Search Tags:#ai agents#resilience#orchestration#retry#failure handling#error management
One-click install
npx skills add https://github.com/PixnBits/SeedClaw --skill retryorchestratorskill
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: RetryOrchestratorSkill
Source: https://github.com/PixnBits/SeedClaw/tree/main/src/skills/sdlc/ops/retry-orchestrator
Command: npx skills add https://github.com/PixnBits/SeedClaw --skill retryorchestratorskill

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses the challenge of handling errors and failures within an AI agent swarm by providing automated detection and recovery orchestration, preventing task failures from halting progress.

Core Features & Use Cases

  • Passive Error Monitoring: Listens for error, failure, timeout, and rejection events on the message bus.
  • Intelligent Recovery: Decides on appropriate actions like retrying, refining prompts, swapping skills, reflecting on errors, or escalating to the user.
  • Use Case: If a skill fails due to a transient LLM timeout, this Skill can automatically retry the task with exponential backoff, or if a critical security violation occurs, it can escalate the issue for user review.

Quick Start

Instruct the RetryOrchestratorSkill to monitor for task failures and initiate recovery actions.

Frequently Asked Questions about RetryOrchestratorSkill

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

FAQPage Schema
How do I automate failure recovery for AI agent swarms?▼

Automate failure recovery by monitoring message bus events for errors and timeouts, tracking failure counts, and emitting structured recovery directives like retries, prompt refinement, or skill swapping.

What is intelligent failure orchestration for AI agents?▼

Intelligent failure orchestration detects task failures in AI agent swarms and decides on appropriate actions, including retrying with exponential backoff, reflecting on errors, escalating, or aborting.

How do I handle transient LLM timeouts in an agent swarm?▼

Handle transient LLM timeouts by passively listening to message bus rejection events and automatically retrying the failed task with exponential backoff to prevent halting progress.

Can I use this retry orchestrator without persistent state or outbound connectivity?▼

Yes, the retry orchestrator operates without persistent state or outbound connectivity, enforcing strict network policies while tracking failure counts and emitting recovery directives.

When should I escalate a task failure instead of retrying it?▼

Escalate task failures instead of retrying when critical security violations occur or when transient errors exceed tracked failure counts, triggering user review or task abortion.

What recovery actions can an error management skill emit for AI agents?▼

An error management skill can emit structured recovery directives including retries, prompt refinement, skill swapping, reflection, escalation, or abortion based on monitored failure events.

Related Skills

Explore More Software Engineering Skills→
chenguojun06-starchenguojun06-star
1

lark-event

Consume real-time Lark events as NDJSON streams with jq filtering.

Community
Advanced
GGEduGGEdu

agent-introspection-debugging

Diagnoses AI agent failures and applies contained recovery actions.

Community
Advanced
TeoSlayerTeoSlayer
7

pilot-role-assign

Assign and manage hierarchical roles within agent swarms via pilotctl.

Community
Intermediate
winsorllcwinsorllc

retry-utils

Execute commands with automated retries using exponential backoff and error conditionals.

Community
Advanced