Agent-Skills.md

Agent Skills: Memory Summarization Skill

Conversation summarization for memory compression and context management

UncategorizedID: a5c-ai/babysitter/memory-summarization

Repository

a5c-ai/babysitter
a5c-aiLicense: MIT
244

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pnpm dlx add-skill https://github.com/a5c-ai/babysitter/tree/HEAD/plugins/babysitter/skills/babysit/process/specializations/ai-agents-conversational/skills/memory-summarization

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plugins/babysitter/skills/babysit/process/specializations/ai-agents-conversational/skills/memory-summarization/SKILL.md

Skill Metadata

Name
memory-summarization
Description
Conversation summarization for memory compression and context management

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