An intelligent, privacy-focused mood tracker that uses natural language processing to analyze daily emotions and generate comprehensive wellness reports.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install xinqing-journal
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install xinqing-journal using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Xinqing Journal?
Xinqing Journal is a sophisticated emotional intelligence tool designed for the Openclaw Skills ecosystem. It enables users to record their daily thoughts using natural language, which the system then processes to automatically identify seven distinct emotional states: Happy, Calm, Excited, Anxious, Sad, Angry, and Tired. By synthesizing raw text into structured data, it provides a clear window into one's mental well-being through automated scoring and intelligent metadata extraction.
Built with a privacy-first philosophy, this skill ensures that all personal reflections remain entirely local. It utilizes local JSON storage with zero network dependencies, making it an ideal solution for users who want to leverage AI-driven insights without compromising their data sovereignty. Whether used for simple daily logging or deep trend analysis, it transforms the traditional diary into a powerful diagnostic tool for personal growth.
Xinqing Journal Use Cases
- Tracking daily mental health patterns through simple, natural language text entries.
- Generating automated weekly or monthly emotional trend reports to identify recurring stress triggers.
- Maintaining a secure, local-only mood diary that avoids cloud-based data collection.
- Visualizing emotional distribution over time using a built-in interactive mood calendar.
- Automatically organizing memories by tagging specific people, locations, and activities mentioned in journals.
How Xinqing Journal Works
- The user provides a natural language entry via the CLI, describing their day or feelings.
- The skill analyzes the input text against a predefined set of emotional keywords and score patterns (e.g., 1-10 points).
- It extracts contextual tags such as people, events, objects, locations, and weather conditions automatically.
- The processed data is saved to a local JSON file using an atomic write mechanism to ensure data integrity.
- Users can then query the database to generate reports, summaries, or visual calendars based on their historical emotional data.
Xinqing Journal Setup
To get started with this skill in your Openclaw Skills environment, ensure you have Python 3.9 or higher installed. No external dependencies are required as it uses the Python standard library.
- Clone the skill into your workspace.
- Ensure the following file structure is present:
xinqing-journal/
├── scripts/journal.py
├── scripts/mood-report.py
└── assets/moods.json
- Start logging your first entry:
python scripts/journal.py add "Today was very productive, feeling great!"
Xinqing Journal Data Schema & Taxonomy
The skill organizes its data in a structured JSON format located at ~/.openclaw/workspace/data/journal/entries.json. The schema includes the following fields:
| Field | Type | Description |
|---|---|---|
id |
String | Unique 8-character identifier |
date |
String | Entry date (YYYY-MM-DD) |
content |
String | Processed journal content |
mood |
String | Primary identified emotion |
score |
Integer | Emotional intensity (1-10) |
tags |
Array | Extracted entities (People, Places, etc.) |
raw_text |
String | Original unedited input string |
created_at |
Timestamp | ISO 8601 creation time |
Xinqing Journal Advanced Features
- Custom Emotion Logic: Users can modify the
assets/moods.jsonfile to redefine emotional keywords, color coding, and emoji representations. - Trend Analysis: Detect long-term emotional fluctuations and receive health suggestions when scores remain low for extended periods.
- Atomic Data Integrity: Employs temporary file swapping during writes to prevent data corruption during power or system failures.
- Multi-Dimensional Reporting: Support for daily, weekly, monthly, and custom-range trend reports with statistical summaries.
- Modular Integration: The core
JournalTrackerclass can be imported as a module into other Openclaw Skills for automated mood-aware workflows.
SKILL.md
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