Personalized Learning Planner

What problem it solves

When learning intent stops at “I want to learn”, this skill turns it into a concrete workflow: confirm the domain, collect baseline level and daily time, generate the first weekly plan, and track completion over time. It is useful for learning paths that need weekly progression and daily execution, especially when a one-off long plan would be hard to maintain.

How it works

The workflow has four parts:
- Domain and goal setup: choose from presets such as office skills, programming, data analysis, product operations, exams, language, finance, or content creation, or define a custom direction.
- Planning and content generation: output the first weekly plan first, then generate daily files like dayNNN_topic.md under ./learning_content/; each file usually covers learning objectives, core concepts, resources, exercises, and notes.
- Progress and memory: use learning_memory.py to update ./learning_content/.learning_memory.json, supporting commands such as “view progress” or “weekly summary”.
- Dynamic adjustment: adapt difficulty, task volume, and schedule based on completion rate, keeping the plan aligned with real capacity.

Fit and limits

It suits engineers, career switchers, or self-learners who want a repeatable learning loop; it is not a substitute for instant tutoring, full course delivery, or autonomous learning without user feedback. Generated files are reference templates, and the actual path still depends on the learner's background. New domains require corresponding reference material.