working-off-of-todo-files

Automating task execution from todo files means having an AI systematically read, prioritize, and complete tasks while updating progress markers like `[/]` for in-progress and `[x]` for completed. This Skill processes `todo.md` or `todo.txt` files in your `ai-notes` directory, breaking down complex work into manageable subtasks and maintaining a single-task focus until each is done.

Yes. Todo files work well for project task management when structured with clear progress markers and subtasks. This Skill enforces single-task focus, explicit progress tracking, and controlled task advancement with your confirmation, making it suited for codebases where tasks must be completed sequentially and status needs updating automatically.

Point the Skill to your `todo.md` or `todo.txt` file in the `ai-notes` directory structure, and it begins reading pending tasks from the top. The AI works through one task at a time, marks progress, and requests your explicit approval before moving to the next item, keeping you in control of workflow advancement.

The Skill decomposes multi-step tasks into subtasks, processes them sequentially while maintaining mental context, and updates each subtask's status independently. Explicit progress markers and clear decision communication help track which subtasks are blocked, in-progress, or complete.

Yes. This Skill processes both `.md` and `.txt` todo files stored in the `ai-notes/**/*/todo.*` path pattern. It reads and validates tasks in either format, applies consistent progress markers, and safely updates files while enforcing structured status tracking across both file types.

Safe file operations include controlled task advancement (requiring user confirmation before proceeding), clear communication of blockers and completion status, and explicit progress markers to prevent unintended state changes. The AI waits for your instruction before modifying tasks or advancing to new work.