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Memory summarization

Skill a5c-ai/babysitter/library/specializations/ai-agents-conversational/skills/memory-summarization

Conversation summarization for memory compression and context managementFrom its SKILL.md

Install
npx -y skills add a5c-ai/babysitter --skill memory-summarization

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SKILL.md

1.5 KB, 211 tokens by cl100k_base, as published. Nobody here has run it

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

  1. Rolling Summary: Update summary with new messages
  2. Hierarchical: Multi-level summarization
  3. Token-Budget: Fit within token limits
  4. Extractive: Key message selection
  5. 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

What ships with it: 1 file

519 B alongside SKILL.md

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