What problem does it solve?
This Skill eliminates context loss and progress tracking failures during complex, multi-step tasks that exceed the AI's attention window or span multiple sessions. It establishes a persistent file-based memory system using three core markdown files to maintain task state, research findings, and session logs.
Core Features & Use Cases
- Structured Task Planning: Creates task_plan.md with phased milestones, status tracking, decision logs, and error history.
- Findings Repository: Maintains findings.md to capture research discoveries, technical decisions, and multimodal insights from browser or visual analysis.
- Progress Logging: Tracks session activity, test results, and operational history in progress.md.
- Automatic Session Recovery: Detects unsynced context from previous sessions via session-catchup.py and prompts the user to restore state.
- Use Case: Ideal for product analysis, complex project decomposition, bug investigation, or any task requiring more than five tool calls where manual context management becomes error-prone.
Quick Start
Use the planning-with-files-zht skill to manage your complex multi-step project by creating task_plan.md, findings.md, and progress.md files that automatically track progress and recover context across sessions.