Coordinates multiple AI agents on shared tasks with explicit handoffs, conflict resolution, and result aggregation—so parallel work stays coherent instead of fragmenting into inconsistent outputs.
Use cases
- Parallel research
- Split implementation
- Coordinated data pipelines
Key features
- Define agent roles and interfaces
- Establish handoff protocols
- Merge outputs with conflict detection
Related
Related
3 Indexed items
Dispatching parallel agents
Splits embarrassingly parallel work—research chunks, file batches, or independent modules—across agents with crisp handoffs back to a single integrator.
Plugin scaffolding
Bootstraps plugin folders, manifests, and baseline files so new Codex or editor extensions start with a consistent, reviewable structure.
Subagent-driven development
Coordinates subagents on slices of a larger plan—ideal when one thread would be too slow but you still need a single accountable integration point.