プラグイン

Memory Fortress for DeepSeek Harness: 5-track layered memory, self-evolution, knowledge graph (SQLite+FTS5), status pill. 本地记忆堡垒：五轨记忆·自我进化·知识图谱·状态灯。

Persistent memory for DeepSeek Harness with curated facts, automatic turn retention, and graph- and vector-ranked recall.

DeepSeek Harness向けのローカルで監査可能なパーソナルメモリ:設定、プロジェクト規約、ワークフロー、エラーの教訓を、変更履歴付きのJSONファイルとしてワークスペースに永続化します。オンボーディング、プロジェクト規約の自動抽出、証拠に基づく教訓に対応します。

DeepSeek Harness にタイムライン記憶を追加します。固定幅の追記専用ファクトログ＋ agent 自身が維持する要約ピラミッドで、固定の読み取り予算のもとで recall コストが記憶量に応じて増大しません。

セッション開始時に注入される長期メモリ：グローバルおよびプロジェクト単位のスコープで嗜好／事実／要約／知識を保持し、`agent/pre-step` による予算付き想起、永続的な JSON ストア。

既存の Claude / ChatGPT 履歴を DSH へ：Claude エクスポート内の memories.json をゼロトークンで即時インポート、ローカルの Claude Code トランスクリプトはエクスポート不要、会話は DSH で設定済みのモデルで蒸留。すべてのメモリはコードでソースと照合された逐語的証拠を伴い、言い換えは破棄してカウント、assistant ターンのみに見つかった証拠は常に保存ではなくレビューへ回す。

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。

Deepseek harness memory

Cross-session long-term memory: captures durable facts from each turn, auto-associates them by shared entity and tag, and recalls with BM25 plus spreading activation over the link graph.

记忆核心（工作区版 memory-eternal-ws）：按 DSH 工作区自动切库的本地 Markdown 记忆库插件。每个项目用自己的 .dsh/memory-vault，跨项目知识走全局库。fork 自 dsh-memory-eternal v0.7.0，保留自动沉淀 / 自动召回 / 知识卡 / 知识图谱 / 审核中心 / 回收站 / 配置页全部功能。

Claude-compatible memory for DeepSeek Harness: a user-chosen memory directory with MEMORY.md index and topic files, the memory tool, and a settings page

Progressive long-term memory for DSH: sharded markdown bodies under ~/.dsh/memory/topics/, with only a live-generated index (shard · count · path · per-entry line numbers) injected into the system prompt — so the prompt cost stays flat however large the m

Read-only enhancer for a file-based long-term memory library (markdown cards in git): a memory_find search tool, a small budgeted memory digest injected into the system prompt, and a settings page with library overview, health-check status and toggles.

Memory archive and prompt viewer for DeepSeek Harness: read back what compaction folded out of context - browse past sessions or Tavern playthrough archives (summary, original text, state) with full-text search - and inspect the prompt each turn actually sent, listing every assembled system section with its order, character count, offset, hash and mutability, plus an assembly map, registry export, and honest diagnostics when a section is empty or its log cannot be read. Optionally provisions a roleplay agent preset.

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.

Layered cross-session memory for DSH that pushes only what changed. The first round injects every active entry, later rounds push only added / updated / removed ones, and nothing at all is injected when nothing changed. Facts and decisions carry semantic keys (one active truth per key), the model may only write to an inbox that a human promotes, an entry can carry a review date that raises a one-time reminder when it comes due, search is relevance-ranked with Chinese matched by bigram, and a sidebar tab tells the lifecycle story instead of just listing files — entries are grouped into awaiting confirmation / in use / archived, viewable by type, tag or date, and the tab can promote a candidate, withdraw or archive a standing entry, restore an archived one and delete a candidate, alongside the global and workspace instruction files and the current injection size. A zero-dependency CLI ships with it, so the store is usable without DSH.

Persistent, searchable, per-project memory for the DeepSeek Harness: decisions, rules, and sprint context in a queryable DuckDB file, rules enforced on every model request, with a full management UI in the Web Client

Polaris Memory: local-first project memory plugin for DeepSeek Harness. Uses per-project .dsh-memory.json; provides memory_read/recall/write/update/delete tools, /memory command and settings UI, with tiered injection (resident user profile + scene-triggered memories with P1/P2/P3 importance), semantic recall (IDF + synonym layer), and a hard-guard mechanism for bottom-line memories (detect deny-semantics -> authorize -> block AI deletion; user can confirm-override).

Integrated memory and context management plugin: four-layer memory system (L2-L4), context compression/trimming/freezing, prompt orchestration, input box UI buttons, and enterprise security with role-based access control.

Bridges the agent to a persistent OKF memory vault over MCP stdio: a Python server (SQLite FTS5 + Markdown) with 10 tools for searching and storing decisions, facts, learnings, conventions, profiles and sources.

Session-memory autopilot: watches DSH sessions and extracts OKF entries in-process through the harness LLM (ctx.llm, deepseek-official by default) at idle, commit, compaction and end checkpoints, storing them via the vault MCP server.

Persistent conversation memory for DeepSeek Harness: memory tab, automatic AI naming, per-AI privacy isolation, sidebar AI names, and automatic experience archiving. A static profile plugin available in every preset without disappearing on restart.

A /remember command that writes facts into the AGENTS.md instruction hierarchy dsh already loads, plus a Memory tab showing which instructions the loader kept within its byte budget.

Agent-curated long-horizon memory (ctx.memory) for DeepSeek Harness: durable project-scoped memory banks with a provider registry and a shipped local backend — a standalone plugin with no upstream harness changes required.