A versatile learning automation skill that retrieves and tracks daily study items across any subject or data format.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install daily-tutor
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install daily-tutor using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Daily Tutor is a robust automation component within the Openclaw Skills framework designed to streamline personalized education. It functions by intelligently scanning user-provided study lists, identifying unlearned material, and presenting it for daily review. Whether you are mastering a new language, memorizing complex mathematical formulas, or reviewing historical dates, this skill adapts to your specific data structure.
The core value of this skill lies in its non-repetitive learning logic. By maintaining a persistent record of progress, it ensures that every session introduces fresh content, maximizing study efficiency. It is built to be used by AI agents or via CLI, making it a perfect fit for developers and students who want to programmatically manage their learning paths.
To integrate this into your environment, ensure you have python3 installed and follow these steps:
# Navigate to your local skills directory
cd path/to/openclaw-skills/daily-tutor
# Populate your data source
touch data/data.json # Add your JSON array of study items here
# Run the skill to get your first lesson
python3 scripts/get_words.py
The skill utilizes a flexible schema-less approach to accommodate diverse subjects:
| File | Role | Format |
|---|---|---|
data/data.json |
Master Source | JSON Array of objects |
data/config.json |
Behavior Settings | JSON object (primary_key, num_items) |
data/learned_items.json |
Progress Log | List of primary keys |
Users can define any fields (e.g., 'term', 'definition', 'example_sentence') and the Openclaw Skills engine will automatically parse and display them.
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