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DeepSeek Harness용 망각 곡선 인플레이스 대화 압축: 최근 턴은 그대로 유지, 중간 턴은 구조적으로 탈수(LLM 미사용), 오래된 턴은 경계 요약 쌍으로 접힘 — 경계 메모리 예산에서의 무경계 대화.

Context curation for DeepSeek Harness: content-aware tool-output slimming, dead-log sweep, pinned user requirements and in-flight work, archive-then-compact with an audit trail.

On-demand memory for DeepSeek Harness: session logs are distilled into layered markdown (a summary, an index and per-topic files), and a mem_query tool returns only the matched entries rather than the whole index. Nothing is injected per turn, there are no dependencies, and every entry keeps a source pointer back to the conversation it came from.

Multi-agent frugality defense plugin: read-ledger dedup metrics, compaction-immune rules, completion gate, cheap-model review lane.