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πŸ¦€ ClawHub

Learning Checkin

by @daizongyu

Daily learning habit builder with check-ins and smart reminders

Versionv3.1.0
Downloads682
Stars⭐ 1
TERMINAL
clawhub install learning-checkin

πŸ“– About This Skill


name: learning-checkin description: Daily learning habit builder with check-ins and smart reminders metadata: { "copaw": { "emoji": "πŸ“š" } }

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:

    /data/
    β”œβ”€β”€ rule.md           - User's customizable rules
    β”œβ”€β”€ records.json      - Check-in history
    β”œβ”€β”€ version.txt       - Current skill version
    β”œβ”€β”€ 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 /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 /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 /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 /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 /learning_checkin.py message 

    Where 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 /learning_checkin.py reminder 

    Returns:

  • should_send - Whether reminder should be sent
  • checked_in - Whether user has already checked in today
  • 7. Update Cron Status

    python /learning_checkin.py update-cron 
    

    When to use: After setting up reminders (optional).

    8. Get Cron Status

    python /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_language is 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 data subfolder 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