Skillget

learn-anything

agent
Guvenlik Denetimi
Basarisiz
Health Uyari
  • License — License: MIT
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Low visibility — Only 5 GitHub stars
Code Basarisiz
  • rm -rf — Recursive force deletion command in tests/test_epub.sh
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  • Permissions — No dangerous permissions requested

Bu listing icin henuz AI raporu yok.

SUMMARY

an agent skill generates good material to learn anything

README.md

Learn Anything

Structured learning framework for any subject — study via CLI with spaced repetition (SM-2). Three-theory pedagogy: Marva Collins, Feynman Technique, Desirable Difficulties.

Features

  • Interactive curriculum creation: LLM-driven syllabus + lesson + MCQ generation
  • CLI study system: read lessons, Feynman explain-back, MCQ drills, spaced repetition
  • SM-2 spaced repetition: optimal recall intervals, mixed-module interleaving
  • Cost-effective: ~$0.10 per course creation, $0 per study session
  • Portable: Markdown files importable into Anki, Obsidian, Notion

Quick Start

  1. Trigger creation: Say I want to learn [topic] or learn.sh init <subject>
  2. Study: learn.sh start <subject> → learn.sh quiz <subject> <module>
  3. Review daily: learn.sh review <subject>

CLI Commands

learn.sh init <subject> [lang]   Create new subject (en|zh|yue)
learn.sh start <subject>         Show overview + modules
learn.sh quiz <subject> <mod>    MCQ drill
learn.sh explain <subject> <mod> Feynman technique prompt
learn.sh feynman <subject> <mod> Alias for explain
learn.sh review <subject>        SM-2 spaced repetition
learn.sh stats <subject>         Progress + retention
learn.sh export <subject>        Anki CSV export
learn.sh epub <subject> [file]   Export course to EPUB book

Subject Structure

subjects/<topic>/
├── syllabus.yaml       # Course spec
├── modules/
│   ├── NN-name/
│   │   ├── lesson.md   # Core content, examples, reframe prompts
│   │   └── quiz.yaml   # 8-10 MCQs
│   └── ...
└── srs/
    ├── deck.json       # SM-2 card state
    └── stats.json      # Study history

Pedagogy

Theory Role
Marva Collins Rigor, repetition, high expectations. Read thoroughly, answer precisely.
Feynman Technique Explain simply → find gaps → refine. Teach concept to imaginary child.
Desirable Difficulties Spaced repetition, interleaved modules, varied MCQ difficulty.

Session Types

Session Duration Focus
LEARN 45-60 min Read lesson, reframe, MCQ drill
EXPLAIN 15-20 min Feynman explain-back, AI gap detection
REVIEW 10-15 min SM-2 spaced repetition (daily)
MIXED 30-45 min REVIEW + LEARN + EXPLAIN combined

EPUB Generation

After creating course content, generate portable EPUB book:

learn.sh epub <subject>              # Full build: assemble + generate
learn.sh epub-regen <subject>        # Regenerate from cached book.md (faster)
learn.sh epub-verify <subject>       # Validate EPUB structure

Agent workflow

  1. Create all modules via content creation protocol (Section 3)
  2. Run learn.sh epub <subject> to assemble lessons + quizzes into single EPUB
    • Script collects all lesson.md + quiz.yaml → writes book.md → generates EPUB
  3. Run learn.sh epub-verify <subject> to validate output
  4. To update after module edits: learn.sh epub-regen <subject> (skips assembly)

Manual alternative: epub.py build <subject-dir> <output> or epub.py from-md <book.md> <output>.

Cost Model

Powered by DeepSeek V4 Flash.

Phase Cost
Scope + syllabus ~$0.01
Per module (~15K tokens) ~$0.004
Full course (20 modules) ~$0.08
Per study session $0

License

MIT

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