plan-tasks

You can generate a dependency-aware execution plan by providing a task list, which the agent analyzes to group tasks into parallel execution batches separated by dependency barriers for optimized throughput.

Assigning non-overlapping file ownership involves partitioning files per task by module or directory, producing a File Ownership Map that prevents conflicts and ensures clear code ownership during parallel execution.

A dependency graph in parallel task planning maps task relationships to identify which tasks can execute concurrently once their dependencies are resolved, forming the basis for parallel execution batches.

Yes, task partitioning applies to software projects, data pipelines, and operations where tasks can be executed in parallel once dependencies are resolved, ensuring efficient and conflict-free execution.

A parallel execution plan outputs a markdown table containing Task ID, Files owned, Depends on, and Description, accompanied by a File Ownership Map and a total task count for clear tracking.

Avoid dependency-based task partitioning for strictly sequential tasks with no parallelizable components, as generating dependency graphs and file ownership maps adds overhead without yielding execution speed benefits.