# Memory Summarization

> Conversation summarization for memory compression and context management

- Skill: `a5c-ai/memory-summarization` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add a5c-ai/memory-summarization`
- Raw SKILL.md: https://api.skillmd.com/api/skills/a5c-ai/memory-summarization/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: a5c-ai (https://skillmd.com/u/a5c-ai)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/a5c-ai/memory-summarization

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# 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