orchestration

Name: orchestration
Availability: InStock
Author: khairulariffinka

Coordinate multiple AI agents across planning, execution, validation, and recovery workflows.

1|Updated Apr 12, 2026

Search Tags:#auditing #orchestration #error-handling #self-healing #ai-agents #workflow-management

Ready to run

npx skills add https://github.com/khairulariffinka/codexen --skill orchestration-khairulariffinka

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: orchestration
Source: https://github.com/khairulariffinka/codexen/tree/main/core/skills/orchestration
Command: npx skills add https://github.com/khairulariffinka/codexen --skill orchestration-khairulariffinka

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Coordinates multiple specialized agents to fulfill complex user requests, coordinating planning, execution, validation, and safe decision-making to maintain system stability and efficiency.

Core Features & Use Cases

Plan generation and task decomposition using planner logic.
Context loading and modular data provisioning for each agent.
Distributed execution across frontend, backend, and QA agents.
Validation through auditor checks and gated commits via git-manager.
Change-propagation when BRS/SRS/SDS docs update, ensuring all components stay in sync.
Built-in self-healing, error handling, timeout strategies, and guardrails for reliability.

Quick Start

Load the orchestration skill and start the planner-agent loop to begin coordinating tasks.

Frequently Asked Questions about orchestration

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

FAQPage Schema

How do I coordinate multiple AI agents to manage complex task workflows?▼

Coordinating multiple AI agents involves using an orchestration layer to decompose plans, load context, execute distributed tasks, and validate outputs with self-healing guardrails to maintain system stability.

What is the best way to handle error recovery and self-healing in AI agent execution?▼

Error recovery in AI agent execution is handled through built-in self-healing mechanisms, applying timeout strategies, error handling, and guardrails to automatically maintain system stability during complex operations.

How do I keep frontend, backend, and QA agents in sync when project documentation updates?▼

To keep distributed agents in sync during documentation updates, you apply change-propagation logic that ensures all components stay aligned when BRS, SRS, or SDS files are modified.

How does gated commit validation work for distributed AI agent tasks?▼

Gated commit validation works by applying auditor checks to distributed execution outputs, ensuring that changes from specialized agents are verified and safe before committing to the system.

Do I need specific dependencies to run an AI agent orchestration loop?▼

No external dependencies are required to run the AI agent orchestration loop. You can load the orchestration skill directly and start the planner-agent loop to begin coordinating tasks immediately.

When should I avoid using AI agent orchestration for task management?▼

You should avoid AI agent orchestration for simple, single-step tasks that do not require distributed execution, context loading, or complex validation guardrails, as the overhead outweighs the benefits.