Memory Distillation

About

The Memory Distillation skill provides a structured framework for Claude to learn from its own interactions by processing session episodes into a refined memory system. It automatically extracts key patterns, pitfalls, and preferences from task outcomes, using a confidence-based scoring system to reinforce successful strategies and prune outdated information. This ensures that the agent retains domain-specific knowledge across multiple sessions, effectively building a custom repository of project-specific best practices and architectural decisions.

Key Features

• Persistent memory storage in markdown format for human readability
• Confidence-based reinforcement and decay mechanics
• Automatic extraction of semantic patterns from session logs
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• Manual and trigger-based distillation workflows
• Categorization of learnings into patterns, pitfalls, and preferences

Use Cases

• Recording and avoiding recurring environment-specific bugs or pitfalls
• Building a project-specific knowledge base of architectural patterns
• Improving agent consistency across long-running development cycles