pi-planning-with-files

Maintain task planning context across sessions by storing core artifacts on disk using a three-file pattern: task_plan.md, findings.md, and progress.md. This separates planning, research, and progress to preserve state reliably.

Recover an AI agent session by restoring context from previously saved planning data on disk. The three-file pattern of task_plan.md, findings.md, and progress.md enables reliable session recovery and immediate work resumption.

Start a persistent markdown planning workspace by initializing the three required files in your project directory: task_plan.md, findings.md, and progress.md. Ready-to-use templates and scripts bootstrap the session and guide execution.

Yes, you can use markdown files for memory management in research tasks. Storing planning artifacts on disk bypasses limited RAM constraints, creating a persistent knowledge base that tracks findings and progress reliably.

No external dependencies are required to implement persistent task planning with markdown. The skill operates independently using standard markdown files and accompanying scripts to manage templates, execution, and session recovery.

Disk-based file pattern task planning is unnecessary for simple, single-step tasks that fit entirely within active memory. It is designed specifically for complex multi-step projects, research tasks, and orchestration requiring session recovery.