Provide implementations of advanced data structures
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a5c-ai/babysitter1.9KUpdated Sep 17, 2026
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memory-summarization
Conversation summarization for memory compression and context management
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See how to installFiles included (2)
- SKILL.md1.5 KB
- README.md519 B
SKILL.md (original)
Review the instructions the agent will receive before you install.
Memory Summarization Skill
Capabilities
- Implement conversation summarization strategies
- Configure rolling summary updates
- Design hierarchical summarization
- Implement token-aware summarization
- Create extractive and abstractive summaries
- Design summary quality evaluation
Target Processes
- conversational-memory-system
- long-term-memory-management
Implementation Details
Summarization Strategies
- Rolling Summary: Update summary with new messages
- Hierarchical: Multi-level summarization
- Token-Budget: Fit within token limits
- Extractive: Key message selection
- Abstractive: LLM-generated summaries
Configuration Options
- LLM for summarization
- Summary token budget
- Update frequency
- Summary template
- Quality thresholds
Best Practices
- Balance detail vs compression
- Preserve key information
- Monitor summary quality
- Test with long conversations
- Handle context window limits
Dependencies
- langchain-core
- LLM provider
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