flashcard-generator
Skill22 starsChanged 3 months agoMITView on GitHub
Turns notes, articles, or a topic into high-quality spaced-repetition flashcards that follow proven formulation principles — atomic, minimum-information, cloze deletions, and active recall — ready to import into Anki or any SRS. Use this skill when the user asks to "make flashcards", "create Anki cards", "turn these notes into flashcards", "help me memorize X", "generate study cards", or "make cloze deletions". Produces clean Q/A pairs and can export to Anki-importable CSV.
5 other projects use a version of this.
Adopted by
Most recently taken up by
- xiongxianfei/skillsmiththeir own version, first seen Nov 1, 2026
- JayRHa/agent-skillsword for word, first seen Oct 15, 2026
- OneWave-AI/claude-skillstheir own version, first seen Sep 21, 2026
- BryceYuuu/open-workflow-skillstheir own version, first seen Sep 5, 2026
- JayRHa/AgentSkillsword for word, first seen Jun 9, 2026
Other versions5 projects use a version of this.
Word for word · 2
- JayRHa/agent-skills★ 12100% same
- JayRHa/AgentSkills★ 12100% same
Edited · 0
None found.
Wrote their own version · 3
- OneWave-AI/claude-skills★ 378same name
- xiongxianfei/skillsmith★ 2same name
- BryceYuuu/open-workflow-skills★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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The file
We split this skill into the rules it gives an agent
1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.
0
Common
Most of the 3 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 64
Keep cards short; brevity speeds reviews and aids retention.
“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Flashcard Generator
Overview
Convert material into flashcards that are actually effective for long-term memory: each card tests one atomic fact, is phrased for active recall, and is unambiguous. Follow the formulation principles in references/card-principles.md (based on SuperMemo's "20 rules" and spaced-repetition research).
Keywords: flashcards, Anki, spaced repetition, SRS, active recall, cloze deletion, memorization, study cards, Q&A, mnemonics, learning.
Workflow
- Identify the learning goal. What must the user be able to recall or do? Cards should serve that goal, not just restate text.
- Extract atomic facts. Break the material into the smallest meaningful units. One card = one fact. Split any "and"/list-laden card.
- Choose a card type per fact (see
references/card-principles.md):- Basic Q/A — for a single fact ("What year…?", "What does X do?").
- Cloze deletion — for facts embedded in a sentence (
The {{c1::mitochondria}} is the powerhouse of the cell). - Reversed — when recall is needed both directions (term↔definition).
- Image/application — for procedures or visual recall.
- Formulate for recall, not recognition. Questions must have a specific, unambiguous answer. Avoid yes/no and "list everything about X" cards.
- Apply the minimum information principle. Simple, short cards review faster and stick better than dense ones.
- Add context only when needed to disambiguate (e.g. tag the subject) — but keep cues out of the answer.
- Review for interference — cards that are too similar cause mix-ups. Differentiate them.
- Export. Produce a clean list and/or run
scripts/to_anki_csv.pyto generate an Anki-importable file (Basic and Cloze note types).
Decision Framework
| Fact shape | Card type |
| Single discrete fact | Basic Q→A |
| Fact inside a sentence/definition | Cloze |
| Term you must recall both ways | Basic + reverse |
| Enumeration/list | Split into N cards, or cloze each item, or use a mnemonic card |
| Procedure/steps | One card per step, or "what comes after step N?" |
Worked Example
Source: "The TCP three-way handshake establishes a connection using SYN, SYN-ACK, and ACK."
Bad (not atomic, recognition-only):
Q: Describe the TCP handshake. → A: It uses SYN, SYN-ACK, ACK to set up a connection.
Good (atomic, recall):
Q: How many steps are in the TCP connection handshake? → A: Three
Q: What does the client send first to open a TCP connection? → A: SYN
Q: What does the server reply with after receiving a SYN? → A: SYN-ACK
Q: What does the client send to complete the TCP handshake? → A: ACK
Cloze: The TCP handshake is {{c1::SYN}} → {{c2::SYN-ACK}} → {{c3::ACK}}.See examples/photosynthesis-cards.md for a full set.
Best Practices
- One fact per card — atomic and minimal.
- Active recall: the question forces retrieval, not recognition.
- Unambiguous answers — exactly one correct response.
- Cloze for context-bound facts; basic Q/A for discrete facts.
- Keep cards short; brevity speeds reviews and aids retention.
- Understand before memorizing — never make cards for things you don't understand.
Common Pitfalls
- Sets/lists on one card ("name all 8 planets") — split them.
- Recognition cards (yes/no, multiple-choice phrased as recall).
- Ambiguous questions with several valid answers.
- Cards that leak the answer in the question's wording.
- Interference from near-identical cards.
- Memorizing without understanding — leads to brittle, useless recall.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

