context-compression
Context Compression Strategies
When agent sessions generate millions of tokens of conversation history, compression becomes mandatory. Optimize for tokens per task (total tokens to complete a task, including re-fetching costs), not tokens per request.
When to Activate
- Agent sessions exceeding context window limits
- Codebases exceeding context windows (5M+ token systems)
- Designing conversation summarization strategies
- Debugging cases where agents "forget" modified files
Three Approaches
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Anchored Iterative Summarization: Maintain structured, persistent summaries with explicit sections for session intent, file modifications, decisions, and next steps. On compression, summarize only the newly-truncated span and merge with existing summary. Structure forces preservation by dedicating sections to specific information types.
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Opaque Compression: Produce compressed representations optimized for reconstruction fidelity. Achieves highest compression ratios (99%+) but sacrifices interpretability.
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Regenerative Full Summary: Generate detailed structured summaries on each compression. Readable output but may lose details across repeated cycles due to full regeneration rather than incremental merging.