graft-multi-agent-batch

To coordinate parallel task execution, this Skill distributes work into bounded slices and delegates them to subagents concurrently. The main agent maintains oversight by health-checking subagents, handling retries, and validating results before final integration.

Distributing workloads in Graft is best handled by slicing complex workflows into bounded segments. This Skill assigns these segments to parallel subagents, enabling concurrent processing while the main agent systematically reviews and validates the returned outputs.

Task slicing divides complex workflows into bounded segments processed by parallel subagents. Main-agent oversight works by continuously health-checking these subagents, retrying failed slices, and validating all processed results before final acceptance.

Yes, you can use multi-agent coordination to process server, web, and documentation slices simultaneously. The Skill delegates these distinct data slices to parallel subagents for concurrent execution while the main agent maintains control over integration and validation.

Parallel multi-agent processing includes built-in mechanisms for retrying failed tasks and ensuring validation is performed. The main agent systematically applies these health-checking mechanisms to validate subagent outputs before accepting the integrated results.

You need parallel subagent coordination when complex workflows require concurrent execution and main-agent oversight. It is essential for scenarios involving multiple bounded data slices that demand systematic review, health-checking, and validation of concurrent operations.