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 nobodyohm-web/Thot --skill memento-flashcardsgit clone --depth 1 https://github.com/nobodyohm-web/ThotWrote 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/nobodyohm-web/thot/memento-flashcards)<a href="https://agentmods.dev/skills/nobodyohm-web/thot/memento-flashcards"><img src="https://agentmods.dev/badge/skills/nobodyohm-web/thot/memento-flashcards/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/nobodyohm-web/thot/memento-flashcards"><img src="https://agentmods.dev/badge/skills/nobodyohm-web/thot/memento-flashcards.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 | $0.00021 | $0.03129 |
| Opus 5.5 | $0.00008 | $0.01252 |
| Sonnet 5.5 | $0.00004 | $0.00626 |
| Haiku 4.5 | $0.00002 | $0.00313 |
Grade A, and why
memento-flashcards 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.
This is a copy
100% identical to memento-flashcards — 19 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 321 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memento Flashcards — Spaced-Repetition Flashcard Skill
Overview
Memento gives you a local, file-based flashcard system with spaced-repetition scheduling. Users can chat with their flashcards by answering in free text and having the agent grade the response before scheduling the next review. Use it whenever the user wants to:
- Remember a fact — turn any statement into a Q/A flashcard
- Study with spaced repetition — review due cards with adaptive intervals and agent-graded free-text answers
- Quiz from a YouTube video — fetch a transcript and generate a 5-question quiz
- Manage decks — organise cards into collections, export/import CSV
All card data lives in a single JSON file. No external API keys are required — you (the agent) generate flashcard content and quiz questions directly.
User-facing response style for Memento Flashcards:
- Use plain text only. Do not use Markdown formatting in replies to the user.
- Keep review and quiz feedback brief and neutral. Avoid extra praise, pep, or long explanations.
When to Use
Use this skill when the user wants to:
- Save facts as flashcards for later review
- Review due cards with spaced repetition
- Generate a quiz from a YouTube video transcript
- Import, export, inspect, or delete flashcard data
Do not use this skill for general Q&A, coding help, or non-memory tasks.
Quick Reference
| User intent | Action |
|---|---|
| "Remember that X" / "save this as a flashcard" | Generate a Q/A card, call memento_cards.py add |
| Sends a fact without mentioning flashcards | Ask "Want me to save this as a Memento flashcard?" — only create if confirmed |
| "Create a flashcard" | Ask for Q, A, collection; call memento_cards.py add |
| "Review my cards" | Call memento_cards.py due, present cards one-by-one |
| "Quiz me on [YouTube URL]" | Call youtube_quiz.py fetch VIDEO_ID, generate 5 questions, call memento_cards.py add-quiz |
| "Export my cards" | Call memento_cards.py export --output PATH |
| "Import cards from CSV" | Call memento_cards.py import --file PATH --collection NAME |
| "Show my stats" | Call memento_cards.py stats |
| "Delete a card" | Call memento_cards.py delete --id ID |
| "Delete a collection" | Call memento_cards.py delete-collection --collection NAME |
What ships with it
2 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 · 321 lines · 21 tokens per session scan A 4504541598e6
memento-flashcards is a skill published in the GitHub repository nobodyohm-web/Thot (0 stars, last pushed 2mo ago), licensed MIT. It adds 21 tokens to every session and 3,129 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to memento-flashcards, differing in 19 lines, and is treated as a copy.
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