agent-coordination

What problem does it solve?

Multi-agent AI systems often struggle with reliable coordination, leading to errors, delays, and the need for manual oversight. This Skill eliminates those issues by replacing unreliable LLM-based coordination with deterministic, script-based enforcement, ensuring your AI agents work together seamlessly.

Core Features & Use Cases

• Deterministic Workflow Enforcement: Guarantees AI agents follow the correct, predefined sequence (e.g., researcher → coder → tester), preventing out-of-order execution and ensuring logical progression.
• Automated Handoffs & Memory Management: Seamlessly passes work products and contextual information between agents via a dedicated AgentDB, eliminating manual data transfer and ensuring continuity.
• Compliance Validation: Automatically checks if an agent can start its task based on workflow rules and validates if its completion meets predefined criteria, enforcing quality and process adherence.
• Use Case: When a researcher agent completes its analysis, this Skill automatically stores its findings and validates that the coder agent can begin implementation, ensuring a smooth, error-free transition without any human intervention.

Quick Start

Use the agent-coordination skill to validate if the coder agent can start for task 5.