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Orchestrate multi-model agents, run workflows, and validate outputs deterministically.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "agent-orchestrator" yet — see the docs or source repo.
Use agent-orchestrator to design a leader-worker flow: have a lead agent break down the task of creating a product launch plan, assign it to copywriting, competitor analysis, and scheduling worker agents, then merge the final result.
A structured multi-agent workflow configuration, task assignment steps, and a merged launch plan.
Use agent-orchestrator to run a code review workflow: first have one model generate review comments, then have a second model verify them, and finally apply deterministic validation rules to check coverage of security, performance, and maintainability.
Executed review results, verification conclusions, and a rule-based validation report.
Using agent-orchestrator, create a structured MCP pipeline for user research processing with four stages: issue classification, summary generation, risk tagging, and result validation, and explain the input and output of each stage.
A staged agent pipeline definition, responsibilities of each node, and executable input/output structures.
Orchestrate multi-model agents, workflows, and deterministic validation for automation.
Orchestrate multiple AI agents to automate complex workflows efficiently.
Enforce structured AI workflows with dependencies, quality gates, and validated outputs.
Orchestrate multi-agent workflows with durable state and replayable execution traces.
Orchestrate multi-model agents for plan-code-review-deliver workflows.
Coordinate multiple AI agents in parallel for debate, review, and synthesis.