planning-with-files

To maintain task state across multiple sessions, this Skill uses persistent markdown files like task_plan.md and progress.md to track decisions and context. This file-based planning approach automatically detects unsynced context from previous sessions to ensure seamless recovery.

The best way to track progress for research tasks requiring more than five tool calls is using a structured markdown workflow. This Skill creates findings.md and progress.md to log discoveries and state, preventing context loss during complex research projects.

To set up file-based planning for complex multi-step development tasks, initialize the planning files in your project directory. This creates the task_plan.md, findings.md, and progress.md files needed to enforce a structured workflow and external memory.

Yes, this task management workflow handles error logging by enforcing a disciplined approach to task execution. It includes a 3-strike protocol and error handling mechanism within the markdown progress files to meticulously log failures during development efforts.

You need external memory for task management when starting large research projects or software development tasks that require numerous tool calls. It prevents context loss by leveraging persistent markdown files to ensure all discoveries and decisions are meticulously logged.

Yes, you need python3 installed as a dependency to run the scripts that implement this markdown-based workflow automation system. The scripts manage the creation and state tracking of your task planning files.