Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add JayRHa/AgentSkills --skill flashcard-generatorgit clone --depth 1 https://github.com/JayRHa/AgentSkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jayrha/agentskills/flashcard-generator)<a href="https://agentmods.dev/skills/jayrha/agentskills/flashcard-generator"><img src="https://agentmods.dev/badge/skills/jayrha/agentskills/flashcard-generator/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jayrha/agentskills/flashcard-generator"><img src="https://agentmods.dev/badge/skills/jayrha/agentskills/flashcard-generator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00113 | $0.01024 |
| Opus 5.5 | $0.00045 | $0.00410 |
| Sonnet 5.5 | $0.00023 | $0.00205 |
| Haiku 4.5 | $0.00011 | $0.00102 |
Grade A, and why
flashcard-generator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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?" |
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 75 lines · 113 tokens per session scan A a2bdfc8203ca
flashcard-generator is a skill published in the GitHub repository JayRHa/AgentSkills (12 stars, last pushed 2mo ago), licensed MIT. It adds 113 tokens to every session and 1,024 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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