Agent Team Organization
Running one agent is easy. Running a team of agents that form around tasks, monitor their own health, vote on decisions, and escalate when they're stuck — that's what separates a toy from a production system. Open Astra handles all of it: dynamic team formation, health monitoring, consensus, reputation tracking, escalation chains, and priority work queues.
ℹAgent teams are different from workspace teams (human users). This section covers how agents are organized into functional teams for task execution.
Why this matters
- Self-organizing — agents form teams automatically based on skill matching and past performance, no manual assignment needed
- Self-monitoring — health dashboards show latency, error rates, and throughput so you catch problems before they affect output quality
- Self-healing — escalation chains route stuck agents to more capable ones (or to humans) instead of letting them spin
- Accountable — reputation scoring surfaces which agents deliver and which need prompt tuning
Team capabilities
| Feature | Description | Docs |
|---|---|---|
| Formation | Auto-form teams based on skill matching and reputation scoring | Formation |
| Health | Monitor latency, error rates, token efficiency, and throughput | Health |
| Consensus | Multi-agent voting and consensus building with configurable majority | Consensus |
| Reputation | Track agent performance with feedback-based scoring | Reputation |
| Escalation | Multi-level escalation chains with timeouts and confidence thresholds | Escalation |
| Work Queues | Priority queues with dequeue, work stealing, and task lifecycle | Work Queues |
Getting started
Start with Team Formation to see how agents auto-assemble, or jump to the Agent Ops use case for a complete walkthrough of running an agent team in production.