Skill: daizongyu/learning-checkin (version 3.1.0)

--- name: learning-checkin description: Daily learning habit builder with check-ins and smart reminders metadata: { "copaw": { "emoji": "📚" } } --- # 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) ```bash 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 ```bash 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 ```bash 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 ```bash 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 ```bash 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 ```bash 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 ```bash python <skill_path>/learning_checkin.py update-cron <times> ``` **When to use:** After setting up reminders (optional). ### 8. Get Cron Status ```bash 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_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


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)