tasks

You can manage project tasks and dependencies using YAML files by querying and manipulating task definitions across feature directories to centralize tracking and reduce manual coordination errors.

The best way to track blocked tasks and visualize dependency hierarchies is to use dependency-aware planning that reveals blocked items and visualizes task structures to guide project decomposition.

You list all current work items and their IDs in a local repo workflow by running the tasks.py CLI, which provides task discovery and status summaries across per-feature and global task files.

Yes, this task tracking approach supports sprint management and roadmap decomposition by applying dependency resolution and state management to ongoing sprints and local repository workflows.

Yes, you can validate YAML schemas for task management through CLI commands, acting as a deterministic wrapper for build, decompose, implement, and task state management operations.

Task dependencies fail to resolve correctly across feature directories when YAML schemas are invalid or when the tasks.py CLI cannot read the global task pool and per-feature files properly.