- Add computeAdaptiveChunkRatio() to reduce chunk size for large messages
- Add isOversizedForSummary() to detect messages too large to summarize
- Add summarizeWithFallback() with progressive fallback:
- Tries full summarization first
- Falls back to partial summarization excluding oversized messages
- Notes oversized messages in the summary output
- Add SAFETY_MARGIN (1.2x) buffer for token estimation inaccuracy
- Reduce MIN_CHUNK_RATIO to 0.15 for very large messages
This prevents compaction failures when conversations contain
unusually large tool outputs or responses that exceed the
summarization model's context window.
