Memoria System

What This Skill Does

The Memoria System is an advanced cognitive memory architecture designed for OpenClaw AI agents. It mirrors the human brain's compartmentalized memory structure, allowing your AI to retain, categorize, and retrieve information with human-like efficiency. By partitioning data into Semantic, Episodic, Procedural, Working, and Indexed layers, the skill ensures that facts, experiences, workflows, and current tasks are organized logically. This structured approach moves beyond simple chat history, enabling the AI to learn from previous interactions, remember specific instructions for complex workflows, and maintain context across long-term sessions.

Installation

To integrate this memory system into your OpenClaw environment, execute the following command in your terminal:

clawhub install openclaw/skills/skills/cuilinshen/memoria-system

Once installed, the system will initialize a directory structure in your designated path. You can verify the installation and current integrity of your memory stores by running ./memory-health-check.sh. Configuration can be managed via the config.json file to set backup retention policies, automatic health check intervals, and custom directory paths.

Use Cases

• Long-Term Project Continuity: Use the system to store project requirements, evolving constraints, and factual knowledge across multiple independent work sessions.
• Automated Routine Management: Store complex multi-step workflows in the Procedural layer, allowing the AI to recall and execute them precisely on command.
• Personalized Assistance: By recording daily interactions in the Episodic layer, the agent can provide personalized insights based on your shared history and preferences.
• Rapid Retrieval: Utilize the Index layer to perform high-speed searches across months of archived facts, events, and session logs.

Example Prompts

1. "Memoria, add a new fact to Semantic memory: The client prefers JSON format for all technical documentation deliverables."
2. "Can you recall the steps for the deployment workflow we defined last month? Check your Procedural memory."
3. "Search my recent episodic memory for any mentions of the project meeting held last Tuesday and summarize the action items."

Tips & Limitations

• Regular Maintenance: Ensure you run ./memory-health-check.sh --fix regularly to maintain the integrity of your index and data files.
• Backups: Always enable the backup feature in your config.json to prevent data loss. Use the --dry-run flag with ./memory-backup.sh if you are testing new backup locations.
• Storage Growth: Keep in mind that as the system collects more episodic data, the disk footprint will grow. Audit your archive periodically to ensure optimal performance.
• Precision: The system relies on accurate categorization. Providing clear, structured input will significantly improve the AI's retrieval accuracy during complex queries.