planning-with-files-zht

Create task_plan.md, findings.md, and progress.md files to track multi-step task progress.

1|Updated Apr 22, 2026
One-click install
npx skills add https://github.com/Herxinsasa/Skills-Collector --skill planning-with-files-zht
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: planning-with-files-zht
Source: https://github.com/Herxinsasa/Skills-Collector/tree/main/planning-with-files/skills/planning-with-files-zht
Command: npx skills add https://github.com/Herxinsasa/Skills-Collector --skill planning-with-files-zht

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

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.

Frequently Asked Questions about planning-with-files-zht

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I maintain context and track progress for complex multi-step tasks across multiple sessions?

Persistent file-based memory solves context loss by creating task_plan.md, findings.md, and progress.md files. These markdown files maintain task state, document research discoveries, and track session activity across multiple sessions.

How do I set up file-based project planning for complex workflows?

File-based project planning requires creating three markdown files: task_plan.md for phased milestones and status tracking, findings.md for research insights, and progress.md for session logs. These files automatically track progress and recover context.

When should I use markdown files for task management instead of relying on session context?

Markdown task management is needed for project planning, research tasks, or bug diagnosis requiring more than five tool calls. Manual context management becomes error-prone in these complex, multi-step workflows, making persistent file-based memory essential.

Does this file-based planning approach support automatic session recovery?

Automatic session recovery detects unsynced context from previous sessions using a dedicated script. It identifies missing state information and prompts the user to restore task progress, ensuring continuity across interrupted complex workflows.

Can I use this task management approach for bug investigation and diagnosis?

Bug investigation and diagnosis are ideal use cases for this task management approach. The system logs errors and documents technical decisions in markdown files, maintaining a clear history of diagnostic steps across multiple investigative sessions.