deepagents-todolist

You can track progress for complex multi-step agent workflows by using the write_todos tool to break down tasks into manageable parts and update their statuses as pending, in progress, or completed.

Task planning for deep agents is managed by decomposing intricate tasks into sequential, exploratory, or parallel steps, allowing agents to dynamically add, remove, or reprioritize items as project requirements change.

Yes, an agent can dynamically adjust a todo list during workflow automation by modifying the task plan to add new steps, remove obsolete ones, or reprioritize work as the multi-step process evolves.

To break down a large software engineering task into manageable steps, you decompose the project into sequential milestones like designing data models and implementing endpoints, then track each item through to completion.

Task decomposition works with parallel and exploratory work patterns by allowing deep agents to structure and track complex, non-linear workflows using the write_todos tool to maintain progress visibility.

An agent may lose track of progress in a multi-step workflow without a structured planning mechanism, which is resolved by using a todo list skill to explicitly mark task statuses and dynamically adjust remaining steps.