An AI concept-learning coach that makes you understand and remember.
Most AI explanations optimize one moment: you ask, it explains, you nod — and three days later it's gone. Magic Memory fixes both halves of learning:
- Understand — it builds intuition before definitions, makes you predict and retrieve instead of passively reading, and catches the exact gap in your mental model.
- Remember — it turns what you understood into flashcards on a spaced-repetition schedule, so concepts survive the forgetting curve instead of evaporating after the chat.
It's built for learning unfamiliar concepts — abstract mechanisms, programming/framework ideas, architecture tradeoffs, and confusing pairs of terms ("what's the difference between X and Y?").
A single learning loop:
calibrate → build intuition → predict → reveal → map → mark boundaries
→ make you retrieve → compress into flashcards → spaced review
- Calibrate first — finds what you already know, why you're learning it, and how deep to go. Crucially, it matches examples to your background (no code snippets thrown at non-programmers).
- Intuition before formalism — analogy, fable, tiny example, or real case first.
- Active recall — it stops and makes you answer before revealing. Nodding along isn't learning.
- Spaced repetition — strong moments become flashcards scheduled by an SM-2 engine.
| File | What it is |
|---|---|
SKILL.md |
The coach's instructions — the portable "brain". This is the prompt. |
references/methods.md |
The five teaching modes, gap-label vocabulary, mastery rubric, learning-science rationale. |
references/review-protocol.md |
Flashcard format, grading scale, the spaced-review workflow. |
scripts/flashcards.py |
A standalone SM-2 spaced-repetition engine. Pure Python 3, zero dependencies. |
Magic Memory is deliberately portable: it's just a text instruction file plus a standalone Python script. Anywhere you can give an AI instructions and run Python, it works. Pick your setup:
Drop the folder into your skills directory:
git clone https://github.com/<you>/magic-memory.git ~/.claude/skills/magic-memoryThen just ask to learn something, or invoke /magic-memory. The agent loads SKILL.md
automatically and runs the flashcard script for you.
Paste the contents of SKILL.md into the Project's custom instructions. Add
references/*.md if you want the deeper methods available. Run the flashcard script locally
when it gives you the commands.
Point the agent at SKILL.md, or copy its contents into your AGENTS.md / system prompt /
custom-instructions field. The agent calls scripts/flashcards.py through its own shell —
nothing Claude-specific is required.
Paste SKILL.md as a system prompt or custom instruction. The model will coach you through
the loop and hand you the flashcards.py commands to run on your own machine for review.
It's fully standalone — use it with or without any AI:
python3 scripts/flashcards.py --help
python3 scripts/flashcards.py add --deck rust --front "Q" --back "A" --hook "memory hook"
python3 scripts/flashcards.py due # what's due today
python3 scripts/flashcards.py grade <id> 5 # self-grade 0–5, auto-reschedulesCards are stored in ~/.magic-memory/cards.json (override with the MAGIC_MEMORY_FILE
env var). Plain JSON — easy to back up or export to Anki later.
The single cheapest way to get more out of this skill: answer out loud, in your own words, using voice-to-text.
When you speak your answer instead of typing a short fragment, you're doing real active recall and Feynman-style self-explanation — the exact things that build memory. It's also far faster, so you actually explain in full sentences instead of one-word replies (which teach you nothing).
- If your device has built-in dictation, turn it on.
- If not, install a speech-input keyboard. The author uses 豆包输入法 (Doubao), whose voice-to-text is excellent — but any good dictation tool works.
This skill is best used as a conversation you talk through, not a wall of text you read.
- Python 3.7+ (standard library only — no
pip installneeded).
MIT — see LICENSE. Free to download, use, modify, and share.