Chalk Labs
Need help deploying memento-flashcards?
Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/tommy-yw-memento-flashcards
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Use cases: spreadsheets, productivity, agent-building
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 26, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/memento-flashcards- Your home directory (~)
What's inside
- Skill name
memento-flashcards- Description
- Spaced-repetition flashcard system. Create cards from facts or text, chat with flashcards using free-text answers graded by the agent, generate quizzes from YouTube transcripts, review due cards with adaptive scheduling, and export/import decks as CSV.
- License
- MIT
- Instructions
- 308 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (3)
- SKILL.md
- memento_cards.py · scripts/
- youtube_quiz.py · scripts/
SKILL.md (first lines)
# 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` |
## Card Storage
Cards are stored in a JSON file at:
```
~/.hermes/skills/productivity/memento-flashcards/data/cards.json
```
**Never edit this file directly.** Always use `memento_cards.py` subcommands. The script handles atomic writes (write to temp file, then rename) to prevent corruption.
The file is created automatically on first use.
## Procedure
### Creating Cards from Facts
### Activation Rules
Not every factual statement should become a flashcard. Use this three-tier check:
1. **Explicit intent** — the user mentions "memento", "flashcard", "remember this", "save this card", "add a card", or similar phrasing that clearly requests a flashcard → **create the card directly**, no confirmation needed.
2. **Implicit intent** — the user sends a factual statement without mentioning flashcards (e.g. "The speed of light is 299,792 km/s") → **ask first**: "Want me to save this as a Memento flashcard?" Only create the card if the user confirms.
3. **No intent** — the message is a coding task, a question, instructions, normal conversation, or anything that is clearly not a fact to memorize → **do NOT activate this skill at all**. Let other skills or default behavior handle it.
When activation is confirmed (tier 1 directly, tier 2 after confirmation), generate a flashcard:
**Step 1:** Turn the statement into a Q/A pair. Use this format internally:
```
Turn the factual statement into a front-back pair.
Return exactly two lines:
Q: <question text>
A: <answer text>
Statement: "{statement}"
```
Rules:
- The question should test recall of the key fact
- The answer should be concise and direct
**Step 2:** Call the script to store the card:
```bash
python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py add \
--question "What year did World War 2 end?" \
--answer "1945" \
--collection "History"
```
If the user doesn't specify a collection, use `"General"` as the default.
The script outputs JSON confirming the created card.
### Manual Card Creation
When the user explicitly asks to create a flashcard, ask them for:
1. The question (front of card)
2. The answer (back of card)
3. The collection name (optional — default to `"General"`)
Then call `memento_cards.py add` as above.
### Reviewing Due Cards
When the user wants to review, fetch all due cards:
```bash
python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py due
```
This returns a JSON array of cards where `next_review_at <= now`. If a collection filter is needed:
```bash
python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py due --collection "History"From Tommy-yw/RunbookHermes, MIT.
More from Tommy-yw/RunbookHermes
- 0.609score
fastmcp
Tommy-yw
Build, test, inspect, install, and deploy MCP servers with FastMCP in Python.
SkillCFreshness: C★ 510Claude Code +9 - 0.609score
ascii-video
Tommy-yw
Production pipeline for ASCII art video — any format.
SkillCFreshness: C★ 510Claude Code +9 - 0.609score
fitness-nutrition
Tommy-yw
Gym workout planner and nutrition tracker.
SkillCFreshness: C★ 510Claude Code +9 - 0.609score
neuroskill-bci
Tommy-yw
Connect to a running NeuroSkill instance and incorporate the user's real-time cognitive and emotional state (focus, relaxation, mood, cognitive load…
SkillCFreshness: C★ 510Claude Code +9 - 0.609score
concept-diagrams
Tommy-yw
Generate flat, minimal light/dark-aware SVG diagrams as standalone HTML files, using a unified educational visual language with 9 semantic color ramps…
SkillCFreshness: C★ 510Claude Code +9 - 0.609score
hermes-atropos-environments
Tommy-yw
Build, test, and debug Hermes Agent RL environments for Atropos training.
SkillCFreshness: C★ 510Claude Code +9 - 0.609score
baoyu-infographic
Tommy-yw
Generate professional infographics with 21 layout types and 21 visual styles.
SkillCFreshness: C★ 510Claude Code +9 - 0.609score
manim-video
Tommy-yw
Production pipeline for mathematical and technical animations using Manim Community Edition.
SkillCFreshness: C★ 510Claude Code +9 - 0.609score
drug-discovery
Tommy-yw
Pharmaceutical research assistant for drug discovery workflows.
SkillCFreshness: C★ 510Claude Code +9 - 0.609score
godmode
Tommy-yw
Jailbreak API-served LLMs using G0DM0D3 techniques — Parseltongue input obfuscation (33 techniques), GODMODE CLASSIC system prompt templates, ULTRAPLINIAN…
SkillCFreshness: C★ 510Claude Code +9 - 0.609score
oss-forensics
Tommy-yw
Supply chain investigation, evidence recovery, and forensic analysis for GitHub repositories.
SkillCFreshness: C★ 510Claude Code +9 - 0.609score
baoyu-comic
Tommy-yw
Knowledge comic creator supporting multiple art styles and tones.
SkillCFreshness: C★ 510Claude Code +9
Signals
- Stars
- 510
- Forks
- 36
- Open issues
- 2
- Last commit (this folder)
- May 1, 2026 (6 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/Tommy-yw/RunbookHermes
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
Same skill elsewhere
Copies of this SKILL.md published by others; search shows only one of them.
More from Tommy-yw
- 0.609score
godmode
Tommy-yw
Jailbreak API-served LLMs using G0DM0D3 techniques — Parseltongue input obfuscation (33 techniques), GODMODE CLASSIC system prompt templates, ULTRAPLINIAN…
SkillCFreshness: C★ 510Claude Code +9 - 0.609score
manim-video
Tommy-yw
Production pipeline for mathematical and technical animations using Manim Community Edition.
SkillCFreshness: C★ 510Claude Code +9 - 0.609score
baoyu-infographic
Tommy-yw
Generate professional infographics with 21 layout types and 21 visual styles.
SkillCFreshness: C★ 510Claude Code +9 - 0.609score
drug-discovery
Tommy-yw
Pharmaceutical research assistant for drug discovery workflows.
SkillCFreshness: C★ 510Claude Code +9 - 0.609score
oss-forensics
Tommy-yw
Supply chain investigation, evidence recovery, and forensic analysis for GitHub repositories.
SkillCFreshness: C★ 510Claude Code +9 - 0.609score
concept-diagrams
Tommy-yw
Generate flat, minimal light/dark-aware SVG diagrams as standalone HTML files, using a unified educational visual language with 9 semantic color ramps…
SkillCFreshness: C★ 510Claude Code +9
Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
Get memento-flashcards running in your business
Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.
Cite this page
memento-flashcards skill. Agent Mart. https://agentmart.dev/skills/tommy-yw-memento-flashcards (last updated 2026-10-24)