Skill: daizongyu/clawwork-learning-checkin (version 1.0.1)

--- name: clawwork-learning-checkin description: Workplace check-in skill for Agent (Claw) with AI-generated personalized greetings metadata: { "OpenClaw": { "emoji": "work" } } --- # Clawwork Learning Check-in Skill A workplace check-in skill that wraps the learning-checkin skill with AI-generated personalized messages. ## Overview This skill provides: - Workplace check-in functionality (wraps learning-checkin) - AI-generated welcome messages (not pre-set templates) - AI-generated daily greetings (not pre-set templates) - Message history to avoid repetition (past 5 days) - Version checking (non-blocking) ## Prerequisites This skill requires the **learning-checkin** skill to be installed. On first run: 1. The skill will check if learning-checkin is installed 2. If not, it will ask the user if they want to install it 3. If approved, install from: https://clawhub.ai/daizongyu/learning-checkin ## Data Storage All data is stored locally in a `data` subfolder next to the skill: ``` <skill_directory>/data/ ├── profile.json - User profile (nickname, language) ├── greetings.json - Message history (to avoid repetition) └── version.txt - Current skill version ``` ## Commands ### 1. Check if learning-checkin is installed ```bash python <skill_path>/clawwork_checkin.py check-installed ``` **Returns:** - `installed` - Whether learning-checkin is installed - `path` - Path where learning-checkin was found - `needs_installation` - True if needs installation - `install_url` - URL to install learning-checkin **Agent action:** - Run this on first interaction - If not installed, ask user: "Would you like me to install the learning-checkin skill first?" - If user agrees, install using appropriate method ### 2. Get Welcome Message Prompt ```bash python <skill_path>/clawwork_checkin.py welcome-prompt ``` **Returns:** - `prompt` - Generation instructions for Agent - `used_recently` - Messages used in past 5 days (to avoid repetition) - `user_language` - User's preferred language - `version` - Current skill version **Agent action:** - Use the prompt to generate a fresh welcome message - Make sure not to repeat any message from `used_recently` - After generating, call `register-welcome` to record it ### 3. Get Daily Greeting Prompt ```bash python <skill_path>/clawwork_checkin.py greeting-prompt ``` **Returns:** - `prompt` - Generation instructions for Agent - `used_recently` - Questions used in past 5 days (to avoid repetition) - `user_language` - User's preferred language **Agent action:** - Use the prompt to generate a fresh greeting question - Make sure not to repeat any question from `used_recently` - After generating, call `register-greeting` to record it ### 4. Register Generated Message ```bash # Register welcome message python <skill_path>/clawwork_checkin.py register-welcome "Your generated message here" # Register daily greeting python <skill_path>/clawwork_checkin.py register-greeting "Your generated question here" ``` **Agent action:** - Call this after generating a message to record it - This ensures it won't be repeated in the next 5 days ### 5. Get Success Message Prompt ```bash python <skill_path>/clawwork_checkin.py success-prompt <streak> ``` **Returns:** - `prompt` - Generation instructions for Agent - `streak` - Current streak count - `special_message` - Special message for milestone streaks (1, 7, 30, 100) - `user_language` - User's preferred language ### 6. Perform Check-in ```bash python <skill_path>/clawwork_checkin.py checkin ``` **Returns:** - `success` - Whether check-in succeeded - `streak` - Current streak count - `nickname` - User's saved nickname - `welcome_prompt` - Prompt for Agent to generate welcome message - `welcome_used_recently` - Past welcome messages to avoid - `greeting_prompt` - Prompt for Agent to generate daily greeting - `greeting_used_recently` - Past greetings to avoid - `success_prompt` - Prompt for Agent to generate success message - `special_streak_message` - Special message for milestone streaks - `user_language` - User's preferred language - `note` - Version check URL **Agent action:** 1. First ensure learning-checkin is installed 2. Run checkin command 3. Use prompts to generate personalized messages: - Generate welcome message (avoid `welcome_used_recently`) - Generate success message (include streak count) - Generate daily greeting (avoid `greeting_used_recently`) 4. Register each generated message using `register-welcome` and `register-greeting` 5. Display messages to user in their preferred language ### 7. Get Version Info ```bash python <skill_path>/clawwork_checkin.py version ``` **Returns:** - `version` - Current version - `check_url` - URL to check for updates - `note` - Instructions **Note:** Version checking is non-blocking. The skill mentions the URL but does not perform actual network checks during normal operation. ### 8. Get/Set User Profile ```bash # Get profile python <skill_path>/clawwork_checkin.py profile # Set nickname python <skill_path>/clawwork_checkin.py set-nickname <name> # Set language preference python <skill_path>/clawwork_checkin.py set-language <lang> ``` ### 9. Get Status ```bash python <skill_path>/clawwork_checkin.py status ``` **Returns:** - `checked_in_today` - Whether user has checked in today - `streak` - Current streak - `total_checkins` - Total check-ins - `nickname` - User's saved nickname ## First-Time Setup Flow 1. **Check if learning-checkin is installed** - Run `check-installed` command - If not installed, ask user to install 2. **Ask for nickname** - "What should I call you? (nickname)" - Save with `set-nickname` command 3. **Note the language used** - Detect from user's first messages - Save with `set-language` command 4. **Use prompts for messages** - Run `welcome-prompt` to get generation instructions - Agent generates message based on prompt - Register with `register-welcome` - Show to user ## Daily Check-in Flow 1. User says something like "check in" or "I'm done" 2. Agent runs `checkin` command 3. Agent receives prompts and used message history 4. Agent generates: - Welcome message (based on prompt, avoiding recent ones) - Success message (based on streak) - Daily greeting (based on prompt, avoiding recent ones) 5. Agent registers generated messages 6. Agent shows messages to user in their language ## Message Generation Guide ### Welcome Message - Purpose: Encourage user to start work - Tone: Energetic, positive - Length: 1-2 sentences - Language: User's preferred language - Must avoid: Past 5 days messages ### Daily Greeting - Purpose: Ask a friendly question after check-in - Tone: Conversational, friendly - Length: 1 sentence - Topics: Their day, plans, feelings, tasks - Language: User's preferred language - Must avoid: Past 5 days questions ### Success Message - Purpose: Congratulate on check-in - Tone: Celebratory, encouraging - Length: 1-2 sentences - Include: Streak count - Special: Use special messages for streaks 1, 7, 30, 100 - Language: User's preferred language ## Version Checking - Version is embedded in the skill - After check-in, skill mentions: "You can check for newer versions at https://github.com/daizongyu/clawwork_learning-checkin" - No automatic network check during normal flow (non-blocking) - User/Agent can manually check GitHub for updates ## Technical Notes - All prompts are in **English** only (no emoji, UTF-8 encoded) - Messages are generated by the Agent, not the skill - Skill tracks history to ensure no repetition within 5 days - Compatible with Windows, Linux, macOS - Uses Python standard library only (no external dependencies) - All file paths are relative to the skill directory - Does not use absolute paths - Designed to work with OpenClaw, copaw, and other tools - Subprocess calls to learning-checkin have 10-second timeout ## Customization Users can customize: - Their nickname (stored in profile.json) - Language preference (for message generation) ## Version Current version: 1.0.1 Check for updates: https://github.com/daizongyu/clawwork_learning-checkin ## Agent Guidelines ### First Interaction 1. Run `check-installed` to verify learning-checkin 2. If not installed: - "I need the learning-checkin skill to work. Would you like me to install it?" - If yes, help install 3. Ask for nickname: "What would you like me to call you?" 4. Remember the language they use 5. Run `welcome-prompt` and generate a welcome message 6. Register with `register-welcome` 7. Prompt for first check-in ### Daily Check-in 1. User indicates they want to check in 2. Run `checkin` command 3. Receive prompts and used message history 4. Generate messages using prompts (avoiding repeats) 5. Register generated messages 6. Show messages to user in their language ### Language - Always respond in the language the user established - Pass `user_language` to the LLM for message generation - If unsure, default to English


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