Learning Check-in Skill

---

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:

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:**

**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:**

3. Status

python <skill_path>/learning_checkin.py status

**Returns:**

4. Get User Language

python <skill_path>/learning_checkin.py env

**Returns:**

**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:**

6. Check Reminder Status

python <skill_path>/learning_checkin.py reminder <time>

**Returns:**

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:**

Default Behavior

Check-in Rule

Reminder Strategy (Suggested)

If user wants reminders, Agent can use any scheduling method:

The skill will check if user already checked in before sending reminders.

Streak System

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

Reminder Implementation (Optional)

If user wants reminders:

Technical Notes

Version

Current version: 3.1.0

GitHub: https://github.com/daizongyu/learning-checkin