Session Compression
If your Claude conversations are bumping up against token limits, this gives you practical patterns to compress them without losing critical context. The progressive compression approach is smart: do nothing until 70% capacity, light cleanup at 85%, aggressive summarization at 95%. You'll find concrete code for LangChain integration, custom compressors, and prompt caching that can cut costs by 90%. The compression ratios are realistic (5-10x for most cases, up to 20x with hierarchical methods) and they're honest about the 2% accuracy tradeoff. Best for long-running support chats or coding sessions, not worth the complexity if your conversations stay under 10 turns.
- skills.sh installs
- 664
- GitHub stars
- 79
- last updated
- Aug 21, 2026
Install
$ npx -y skills add bobmatnyc/claude-mpm-skills --skill session-compression --agent claude-codeInstalls into .claude/skills of the current project.
Files
AI Session Compression Techniques
Summary
Compress long AI conversations to fit context windows while preserving critical information.
Session compression enables production AI applications to manage multi-turn conversations efficiently by reducing token usage by 70-95% through summarization, embedding-based retrieval, and intelligent context management. Achieve 3-20x compression ratios with minimal performance degradation.
Key Benefits:
- Cost Reduction: 80-90% token cost savings through hierarchical memory
- Performance: 2x faster responses with compressed context
- Scalability: Handle conversations exceeding 1M tokens
- Quality: Preserve critical information with <2% accuracy loss
When to Use
Use session compression when:
- Multi-turn conversations approach context window limits (>50% capacity)
- Long-running chat sessions (customer support, tutoring, code assistants)
- Token costs become significant (high-volume applications)
- Response latency increases due to large context
- Managing conversation history across multiple sessions
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- Repository
- github.com/bobmatnyc/claude-mpm-skills
- Category
- AI & Agent Building
- First seen
- Jun 3, 2026
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