A privacy-first mental health tool designed to help users manage depression through mood tracking and manageable behavioral activation tasks.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install depression-support
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 depression-support 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 Depression Support?
The Depression Support skill is a dedicated tool within the Openclaw Skills ecosystem designed to assist individuals navigating the challenges of low mood and depression. It operates on the core principle of behavioral activation—the idea that taking small actions can eventually lead to improved emotional states. By providing a structured yet gentle interface, the skill helps users break the cycle of inactivity that often accompanies depressive episodes.
This skill prioritizes absolute privacy, ensuring that all mood logs, personal notes, and habit patterns are stored locally on the user's device. It serves as a non-judgmental companion that encourages self-compassion, providing reminders for basic self-care and celebrating micro-wins that might otherwise go unnoticed. By using Openclaw Skills for mental health support, developers and users can leverage AI to build resilience and maintain a consistent wellness routine without compromising sensitive data.
Depression Support Use Cases
- Managing daily motivation when experiencing symptoms of depression or low energy.
- Tracking emotional trends over time to identify specific triggers or effective coping mechanisms.
- Receiving low-friction suggestions for self-care when the mental load of decision-making is too high.
- Documenting small daily accomplishments to build a record of momentum and progress.
- Accessing a private, localized environment for mental health journaling and check-ins.
How Depression Support Works
- Initialize the session by using triggers such as low mood or depression help to activate the skill's empathetic response mode.
- Complete a mood check-in by providing a rating or descriptive word, which the skill logs in a local data store.
- Request micro-tasks based on current energy levels, receiving 3-5 suggestions that require minimal willpower to start.
- Log small wins throughout the day to create a positive feedback loop and evidence of activity.
- Query your history to view patterns and trends, helping you understand which activities correlate with better mental health outcomes.
Depression Support Setup
To integrate this support tool into your agent environment, follow the standard installation process for Openclaw Skills. Ensure your local storage permissions are configured to allow the skill to save your mood history.
openclaw install depression-support
Once installed, you can start your first check-in by typing or saying: I want to log my mood.
Depression Support Data Schema & Taxonomy
The skill maintains a highly structured local schema to track progress while maintaining total privacy. The data is organized into the following components:
| Component | Data Tracked | Storage Location |
|---|---|---|
| Mood History | Timestamped ratings (1-10) and contextual notes. | Local JSON/SQLite |
| Activity Log | Completed micro-tasks and behavioral activation wins. | Local Directory |
| Pattern Analytics | Weekly/Monthly trend data and correlation points. | Local Cache |
| Self-Care Metrics | Status of basic needs: hydration, sleep, and movement. | Local State |
Depression Support Advanced Features
- Customizable micro-task libraries tailored to physical, social, creative, or cognitive preferences.
- Proactive self-care reminders that trigger based on time of day or duration since the last check-in.
- Deep pattern recognition within the Openclaw Skills framework to highlight long-term recovery trends.
- Multi-level energy scaling that adjusts suggestions from zero-energy tasks to more involved activities.
- Integration with local notification systems for consistent, non-intrusive mental health check-ins.
SKILL.md
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