メモリ

DeepSeek Harness 向けのユーザー設定メモリ。memory_get/memory_update ツールとシステムプロンプトへの注入により、ユーザープロファイルを永続化します。

OpenAI Codex のメモリ・スキル・設定を DeepSeek Harness に橋渡しします。

md/txt/docx/pdf から監査可能なナレッジベースパック(SQLite FTS5)を構築します。決定的な検索と原文読み取りに対応。

プロジェクト単位のセッション間メモリ。最初のユーザーメッセージに PROJECT.md のスナップショットを注入し、memory_remember ツールと ReAct タスク後の自動振り返りを提供します。プロジェクトごとに独自のメモリファイルを保持します。

DSH のロスレスなセッションログ上に構築された、引用付きメモリ。要約された事実には `(sessionId, eventRange)` の引用情報が付き、元のログの該当箇所を正確に展開できます。

给 DeepSeek Harness 补上时间轴记忆：定宽只追加的事实日志 + agent 自己维护的摘要金字塔，固定阅读预算下 recall 成本不随记忆量增长。

Native DeepSeek Harness (dsh) plugin: hybrid local and XMemo cloud memory for Cordis-based agents.

Native StrataGate layered long-term memory for DeepSeek Harness

Evidence-backed, human-approved project memory for DeepSeek Harness

DSH 全局经验插件（骨架）：自动探测本地依赖/便捷路径/网络/磁盘并沉淀为跨会话环境档案，订阅 session/event 折叠每会话统计，把低开销摘要注入每轮系统提示，env_profile 工具按需查全量——减少重复探测、加快会话、降低 token 消耗。

Automatic cross-session GoodMemory recall and writeback for DeepSeek Harness

DeepSeek Harness settings-pro plugin: IM bridge (Telegram/WeChat), DeepSeek usage, cross-restart memory, desktop pets, and a vision bridge

DSH plugin: automatic dual-peer Honcho v3 memory, contextual recall, search, reasoning, conclusions, and health diagnostics

Long-term memory injected at session start: preferences/facts/summaries/knowledge in global and per-project scopes, budgeted recall via `agent/pre-step`, durable JSON store.

Enhanced auto-compaction defaults for DeepSeek Harness agent presets: apply tuned threshold/retention budgets and per-model policies with one command, idempotent with backups and rollback.

Brings your existing Claude / ChatGPT history into DSH: instant zero-token import of the memories.json inside a Claude export, local Claude Code transcripts with no export needed, and conversations distilled through the model you already configured in DSH. Every memory carries verbatim evidence checked against the source by code — a paraphrase is dropped and counted, and evidence found only in the assistant turns is always routed to review rather than stored.

Conversation history recall for DSH: three-layer (literal/fuzzy/semantic) retrieval over every past session's original text, fully local & offline — AI never forgets what you told it. One-command install via `dsh.bundle.patch`, semantic layer runs in a worker thread.

Turns local markdown and text documents into a queryable knowledge base with hybrid semantic and keyword search, citation verification, and source injection.

Agent tools for a self-hosted mem0 server: add, search, get, update, delete, history, reset and status memories, with a settings-panel configuration card.

Cross-session plaintext memory: deterministic BM25 keyword recall (no embeddings), memory_save/list/search/confirm/forget tools behind a human-confirm gate, and global + project-scoped JSON stores that follow your git repo.

Provides local and remote knowledge bases with project- and session-scoped recall, controlled write-back, and an embedded Web management console.

Layered memory pipeline for DSH: auto-distills conversations into atomic facts, scene summaries and a persona profile (L0–L3), with hybrid BM25 + vector retrieval, chat/work family separation, and context injection before each model step.

Rewrites each request against a learned prompt profile and automatically updates habits, anti-hallucination rules, and learning records.

Automatic, local-first cross-session memory for DeepSeek Harness: layered Event/Element cards, evidence-gated recall, and expansion back to original turns and tool results.