memento-flashcards

Manage local spaced-repetition flashcards with JSON storage and Python scripts.

2|1|Updated Jul 14, 2026
One-click install
npx skills add https://github.com/heysuhas/hermes_cli --skill memento-flashcards-heysuhas
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: memento-flashcards
Source: https://github.com/heysuhas/hermes_cli/tree/main/optional-skills/productivity/memento-flashcards
Command: npx skills add https://github.com/heysuhas/hermes_cli --skill memento-flashcards-heysuhas

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires youtube-transcript-api, and includes scripts (resource) components.

What problem does it solve?

This skill solves the challenge of information retention by providing a local, file-based spaced-repetition system that turns factual content into structured, adaptive learning sessions.

Core Features & Use Cases

  • Spaced Repetition: Automatically schedules reviews based on your performance to optimize memory retention.
  • YouTube Integration: Instantly generates 5-question quizzes from YouTube video transcripts.
  • Free-Text Grading: Uses the agent to evaluate your answers in real-time, providing feedback and correcting misconceptions.
  • Use Case: Use this to memorize historical dates, learn a new language, or quiz yourself on the key takeaways from a technical podcast.

Quick Start

Ask the agent to quiz you on a specific YouTube video URL to generate and start a flashcard session immediately.

Frequently Asked Questions about memento-flashcards

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate flashcards from a YouTube video transcript?▼

To generate flashcards from a YouTube video transcript, you provide the video URL to the agent, which then uses the youtube-transcript-api to instantly create a 5-question quiz session for active recall.

How does spaced repetition scheduling work for memory retention?▼

Spaced repetition scheduling optimizes memory retention by automatically adjusting the review frequency of flashcards based on your real-time performance grading, ensuring factual content is reviewed at optimal intervals.

Can I create custom Q/A pairs from text instead of using YouTube videos?▼

Yes, you can create custom Q/A pairs directly from text. The system manages a local spaced-repetition flashcard setup that turns factual content into structured, adaptive learning sessions without requiring video input.

Do I need a specific Python environment to run local flashcard scripts?▼

Yes, you need a standard Python runtime environment to execute the local scripts and manage the JSON-based data storage required for the spaced-repetition flashcard system and automated quiz generation.

How does the agent evaluate answers during a flashcard quiz session?▼

The agent evaluates answers during a flashcard quiz session using free-text grading, providing real-time feedback and correcting misconceptions directly within the local learning environment.

What are the limitations of using JSON-based data storage for flashcards?▼

Using JSON-based data storage for flashcards limits the system to local file-based management, which means it does not support cloud synchronization or multi-device access, restricting learning sessions to your local Python environment.