Why does the skill log errors in the task plan?

Logging errors builds a persistent knowledge base for the current session, allowing the AI to learn from its mistakes and avoid repeating them during complex debugging.

What is the 3-file pattern in this skill?

It is a strategy that uses task_plan.md for tracking progress, notes.md for research findings, and a final deliverable file to keep the AI's context focused and organized.

Does this skill work with existing projects?

Yes, it initializes markdown files within your current working directory to manage and track the specific task you are currently working on.

How does this improve AI performance?

It offloads large amounts of data to disk instead of the active context window, preventing 'context stuffing' while keeping goals visible through frequent file reads.

When should I use this context management skill?

It is best used for any task requiring three or more steps, deep research, or workflows involving multiple tool calls where state persistence is critical.

Context Management & Task Planning

Name: Context Management & Task Planning
Author: memorysaver

bymemorysaver

Productivity & Workflow

Implements a persistent, file-based workflow for complex task planning and execution using the Manus-style 3-file pattern.

About

This skill optimizes Claude's operational efficiency by utilizing persistent markdown files as externalized working memory. By implementing the 'Manus' pattern—consisting of a task plan, research notes, and a deliverable file—the skill ensures that multi-step projects remain structured and goal-oriented. This approach prevents context window saturation, improves error recovery through dedicated logging, and maintains a clear audit trail of decisions made during long-running tasks, making it essential for complex software engineering and research workflows.

Key Features

Standardized 3-file pattern for state management (task_plan.md, notes.md, deliverable.md)
0 GitHub stars
Persistent phase tracking with checkboxes and status updates
Externalized research storage to keep the active context window lean
Structured error logging to prevent repetitive mistakes in recursive tasks
Pre-decision goal refreshing to ensure project alignment

Use Cases

Executing multi-step software engineering projects or complex refactors
Managing autonomous workflows that require state persistence across tool calls
Conducting deep research and synthesizing technical findings into documentation

About

Key Features

Standardized 3-file pattern for state management (task_plan.md, notes.md, deliverable.md)
0 GitHub stars
Persistent phase tracking with checkboxes and status updates
Externalized research storage to keep the active context window lean
Structured error logging to prevent repetitive mistakes in recursive tasks
Pre-decision goal refreshing to ensure project alignment

Use Cases

Executing multi-step software engineering projects or complex refactors
Managing autonomous workflows that require state persistence across tool calls
Conducting deep research and synthesizing technical findings into documentation