openclaw-memory-fix

What This Skill Does

OpenClaw Memory Fix is a sophisticated cognitive architecture upgrade for the OpenClaw AI agent, designed to transition the agent from a stateless conversational model to an entity with long-term retention capabilities. By implementing a proprietary four-tier memory structure (Short-term, Episodic, Semantic, and Long-term), this skill allows the agent to build depth over time. The system employs dynamic decay algorithms that automatically prune irrelevant information while cementing core user preferences and high-value knowledge. Furthermore, it integrates a hybrid retrieval system combining vector indices and knowledge graphs to ensure that retrieved context is highly relevant, sentiment-aware, and temporally accurate. This transforms the agent from an assistant into a consistent collaborator that truly 'knows' the user.

Installation

To integrate this module into your workspace, execute the following command in your terminal: clawhub install openclaw/skills/skills/githubxiaohei/openclaw-memory-fix After installation, ensure you create a memory/ directory in your workspace root, which will store the individual L1 through L4 hierarchical folders and your config.json settings.

Use Cases

• Project Continuity: Ideal for long-term software development where the agent needs to remember context, project constraints, and coding style preferences across weeks of development.
• Personalized Assistance: Perfect for users who want the AI to remember their dietary preferences, meeting habits, or specific formatting requirements for documentation.
• Knowledge Management: Useful for maintaining a growing base of personal project insights that are validated through the system's L3 to L4 migration protocol.

Example Prompts

• "Review our past architectural decisions from last week and check if they align with the current constraints."
• "What do you remember about the project guidelines I set when we started this sprint?"
• "Forget the context of our last brainstorming session, but keep the core project requirements in long-term memory."

Tips & Limitations

• Tips: Use the node scripts/memory.js status command regularly to monitor the migration cycles. If you find the agent forgetting important details, consider manually triggering migrations or adjusting your decay parameters in config.json.
• Limitations: The system relies on local file storage. Ensure your workspace permissions allow for write access to the memory directory. Excessive memory accumulation might impact performance in very constrained environments, so allow the dynamic decay mechanism to run as designed.