← Back to Skills Marketplace
ivangdavila

Flashcards

by Iván · GitHub ↗ · v1.0.0
cross-platform ✓ Security Clean
1221
Downloads
2
Stars
2
Active Installs
1
Versions
Install in OpenClaw
/install flashcards
Description
Create effective flashcards with optimal formatting, spaced repetition integration, and memory science principles.
README (SKILL.md)

Card Formulation Rules

One fact per card: Never combine multiple concepts. "What is X?" not "What are X, Y, and Z?"

Atomic questions: Break complex topics into smallest testable units. Each card tests exactly one thing.

Bidirectional cards for definitions: Create both term→definition AND definition→term to prevent recognition-only learning.

Use cloze deletions for facts: "The mitochondria is the {{c1::powerhouse}} of the cell" forces active recall.

Question Types by Effectiveness

Best retention: Why/How questions that require understanding, not just recall.

Good retention: Fill-in-the-blank, definition recall, process steps.

Weak retention: Yes/No questions, multiple choice (use sparingly).

Avoid: Questions answerable by pattern matching or elimination.

Anki-Specific Formatting

TSV import format: front back tag1 tag2 — tabs separate fields, spaces separate tags.

Cloze syntax: {{c1::answer}} for single deletion, {{c1::first}} and {{c2::second}} for multiple.

Image occlusion: Use for diagrams, maps, anatomical images. Hide labels, reveal on flip.

Tags for organization: Use hierarchical tags subject::topic::subtopic for filtered study.

Memory Science Integration

Minimum information principle: Simpler cards = better retention. If card feels complex, split it.

Personal connection: Add context from your experience. "X reminds me of Y" strengthens encoding.

Concrete over abstract: "Paris is capital of France" beats "Capitals are important cities."

Imagery when possible: Visual descriptions enhance memory. "Mitochondria = bean-shaped power plant."

Common Mistakes

Too much text on back: Keep answers under 20 words. Long answers = weak recall signal.

Orphan cards: Cards without context fail. Include source/chapter in tags.

Copy-paste from textbook: Rephrase in your own words. Understanding before memorization.

Skipping hard cards: Difficulty means you need it most. Never suspend without replacement.

Output Formats

Anki TSV: question answer tag1 tag2

Quizlet import: Question and answer separated by tab, cards separated by newline.

Markdown table: For review before import.

| Front | Back | Tags |
|-------|------|------|
| Q1 | A1 | topic |

Spaced Repetition Settings

New cards/day: 10-20 for sustainable learning. More causes review pile-up.

Review intervals: Trust the algorithm. Don't manually reschedule.

Again vs Hard: "Again" = complete failure (resets interval). "Hard" = struggle but recalled.

Leeches: Cards failed 8+ times need rewriting, not more repetition.

Usage Guidance
This skill appears low-risk and internally consistent: it only provides flashcard-writing rules and export formats, and it asks for no installs or credentials. Because the source/homepage is unknown, review generated cards before importing them into your study tools and avoid putting sensitive personal data into cards. If you prefer that the model not autonomously invoke this skill, disable model invocation or require explicit user invocation in your agent settings.
Capability Analysis
Type: OpenClaw Skill Name: flashcards Version: 1.0.0 The OpenClaw AgentSkills skill bundle is benign. It consists of standard metadata in `_meta.json` and detailed instructions in `SKILL.md` for an AI agent on how to create effective flashcards. The `SKILL.md` content is purely instructional, focusing on formatting, memory science principles, and common mistakes, without any evidence of malicious intent, data exfiltration, unauthorized execution, persistence mechanisms, or prompt injection attempts designed to compromise the agent or its environment.
Capability Assessment
Purpose & Capability
The name and description match the SKILL.md content: guidance for creating flashcards, Anki/Quizlet formats, and spaced-repetition advice. There are no unrelated environment variables, binaries, or install steps requested.
Instruction Scope
The SKILL.md contains only content-creation rules, formatting examples, and study recommendations. It does not instruct the agent to read system files, access environment variables, call external endpoints, or transmit data outside the user context.
Install Mechanism
No install spec or code files are present; this is instruction-only so nothing is downloaded, extracted, or written to disk by design.
Credentials
No environment variables, credentials, or config paths are requested — proportional and appropriate for a purely authoring/formatting skill.
Persistence & Privilege
The skill does not set always:true or other elevated persistence flags. Model invocation defaults to allowed, which is reasonable for a non-sensitive, instruction-only skill.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install flashcards
  3. After installation, invoke the skill by name or use /flashcards
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release
Metadata
Slug flashcards
Version 1.0.0
License
All-time Installs 2
Active Installs 2
Total Versions 1
Frequently Asked Questions

What is Flashcards?

Create effective flashcards with optimal formatting, spaced repetition integration, and memory science principles. It is an AI Agent Skill for Claude Code / OpenClaw, with 1221 downloads so far.

How do I install Flashcards?

Run "/install flashcards" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Flashcards free?

Yes, Flashcards is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Flashcards support?

Flashcards is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Flashcards?

It is built and maintained by Iván (@ivangdavila); the current version is v1.0.0.

💬 Comments