A personal AI-driven emotional tracking and analysis tool that identifies long-term psychological trends, triggers, and effective coping strategies.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ai-mood-journal
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install ai-mood-journal using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Mood Journal acts as your private AI psychological consultant, designed to help you build self-awareness through daily reflection. By capturing your emotional state, physical sensations, and events throughout the day, the system transforms unstructured input into meaningful psychological data.
Beyond simple logging, the tool uses advanced analysis to reveal hidden patterns in your mental well-being. It helps you identify recurring triggers, evaluates the effectiveness of your coping mechanisms, and provides actionable, non-judgmental suggestions to improve your emotional resilience over time.
To integrate the Mood Journal into your agentic workflow, follow these steps:
# Ensure Openclaw environment is initialized
openclaw init
# Install the mood-journal skill
openclaw install mood-journal
# Configure your user profile for trend tracking
openclaw config mood-journal --user-id="your-id"
The skill maintains a structured taxonomy to organize emotional data for both immediate feedback and longitudinal analysis.
| Field | Type | Description |
|---|---|---|
| mood_score | String | Numerical intensity (e.g., 7/10) |
| primary_emotion | String | The dominant emotional state recorded |
| trigger | String | The event or thought causing the state |
| insight | String | AI-generated behavioral pattern observation |
| suggestion | String | Actionable advice based on historical trends |
Long-term tracking files are stored as JSON blobs containing total_entries, average_mood, and top_triggers lists.
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