learning-checkin
v3.1.0Daily learning habit builder with check-ins and smart reminders
Installation
Learning Check-in Skill
Help users build a daily learning habit through simple check-ins and intelligent reminders.
Overview
This skill enables users to track their daily learning with: - Simple daily check-in (just say "I'm done" or "check-in complete") - Automatic streak tracking - Optional smart reminders
Data Storage
All data is stored locally in a data subfolder next to the skill:
<skill_directory>/data/
├── rule.md - User's customizable rules
├── records.json - Check-in history
├── version.txt - Current skill version
├── cron_status.json - Reminder configuration status
└── reminder_log.json - Reminder sending log
The data folder is automatically created on first use.
Commands
1. Initialize (First Time)
python <skill_path>/learning_checkin.py init
Returns:
- welcome_message - Welcome text for the user
- environment - Only contains user_language (for message display)
- reminder_strategy - Suggested reminder times
- cron_status - Current reminder configuration status
Agent action: 1. Run the init command 2. Show welcome message and explain the check-in process 3. Ask user if they want daily reminders 4. Ask user to start their first check-in
2. Check-in
python <skill_path>/learning_checkin.py checkin
Returns:
- success - Whether check-in was recorded
- streak - Current streak count
- message - Celebration message (in English, translate to user's language)
3. Status
python <skill_path>/learning_checkin.py status
Returns:
- checked_in_today - Whether user has checked in today
- streak - Current streak count
- total_checkins - Total days checked in
- message - Status message (in English)
4. Get User Language
python <skill_path>/learning_checkin.py env
Returns:
- user_language - Detected language (zh/en)
Why needed: Only to display messages in the user's preferred language.
5. Get Reminder Message
python <skill_path>/learning_checkin.py message <time>
Where <time> is one of: 09:00, 17:00, 20:00
Returns:
- message - Reminder text (in English, translate to user's language)
6. Check Reminder Status
python <skill_path>/learning_checkin.py reminder <time>
Returns:
- should_send - Whether reminder should be sent
- checked_in - Whether user has already checked in today
7. Update Cron Status
python <skill_path>/learning_checkin.py update-cron <times>
When to use: After setting up reminders (optional).
8. Get Cron Status
python <skill_path>/learning_checkin.py cron-status
Returns:
- configured - Whether reminders are set up
- times - Configured reminder times
Default Behavior
Check-in Rule
- User checks in once per day
- Simply tell the Agent "I'm done" or "check-in complete"
Reminder Strategy (Suggested)
If user wants reminders, Agent can use any scheduling method: - Evening (20:00) is recommended as default - Or user's preferred time
The skill will check if user already checked in before sending reminders.
Streak System
- Consecutive days = streak
- Miss a day = streak resets
Customization
Users can edit the rule.md file (in the data folder) to customize reminder messages.
Version
See GitHub releases: https://github.com/daizongyu/learning-checkin/releases
Agent Guidelines
First Interaction (Welcome)
The Agent should: 1. Be warm and encouraging 2. Explain the simple check-in process 3. Ask if user wants daily reminders (optional feature) 4. Ask: "Ready to start your first check-in?"
Check-in Interaction
- Translate messages to user's language
- Celebrate the check-in
- Show streak count
Reminder Implementation (Optional)
If user wants reminders:
- Agent decides how to implement (cron, native scheduler, etc.)
- The skill provides reminder and message commands
- Check if user already checked in before sending
Technical Notes
- Data collection: Only
user_languageis collected for message display - All messages are in English - Agent translates to user's language
- All file paths use UTF-8 encoding
- Compatible with Windows, Linux, macOS
- Data stored in
datasubfolder next to the skill - No external network requests from the skill
- No automatic scheduling - Agent decides implementation
- No external dependencies (Python standard library only)
Version
Current version: 3.1.0
GitHub: https://github.com/daizongyu/learning-checkin