agent-coordination

Coordinate AI agents by enforcing deterministic execution order through script-based rules that validate preconditions, manage shared memory via AgentDB, and automate handoffs between agents like researcher, coder, and tester. This ensures agents execute in the correct sequence without out-of-order execution or manual intervention.

Use automated handoff mechanisms that pass work products and context between agents through a dedicated memory store. The Skill validates completion criteria before the next agent starts, eliminating manual data transfer and ensuring continuity across the workflow.

Apply structured validation checkpoints that automatically check if an agent meets preconditions before starting and if its output satisfies completion criteria. This guarantees process adherence and traceability without requiring manual oversight.

Yes. Deterministic, script-based enforcement replaces unreliable LLM-based coordination, guaranteeing agents follow predefined sequences and preventing errors, delays, and the need for manual oversight in multi-agent task pipelines.

No. Automated memory management via AgentDB stores and retrieves task summaries between agents, eliminating manual data transfer and ensuring seamless continuity without human intervention.

Reliable coordination prevents out-of-order execution, ensures logical progression through stages like research, coding, and testing, and automatically validates that each agent's output meets requirements before the next agent begins, reducing errors and delays.