vilicvane/dsh-plugin-turn-memory

README excerpt

dsh-plugin-turn-memory Turn-granular context memory for DeepSeek Harness: step 1 of a two-step context-compression plan. Every time a root session's turn completes, a one-shot fork (same model as the conversation, sharing its warm request prefix) writes an independent flowing summary of that turn alone. At the pre-step of the next user-initiated turn, each summarized turn is replaced on the model-visible surface by its summary checkpoint. The newest user message always stays verbatim, and the raw events remain in the append-only log for replay and recall. The expand turn tool recalls a turn's full transcript in three modes: - fork — the main model continues from the conversation state at that turn, with the warm request prefix; best for deep questions about a recent turn. - subagent — a cheap model reads the turn's full text and answers a targeted question or produces a directed summary. - raw — the turn's full text is returned directly into the conversation; very large turns are truncated; last resort. The model picks the mode itself (default auto routes recent turns to fork and older turns to subagent). Summary format (version 3) Each checkpoint is a single user message: Timeline…

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