Memory

Human-readable Markdown memory for DeepSeek Harness: user-level (~/.deepseek-harness/MEMORY.md) + workspace-level memory injected every turn, auto daily-log writing with distillation, bridges existing WorkBuddy/CodeBuddy memory dirs, memory_note / memory_note_user / memory_read tools with built-in dedup, and a bilingual settings page. Plain-text storage, no database.

A long-term memory plugin for DeepSeek Harness. Every turn is judged and stored into a local SQLite (utterance / event / version / stage / decision), with a browsable panel.

给 DeepSeek Harness 的跨会话记忆：按工作区隔离、跨会话共享的长期记忆。常驻 prompt 的只有浅层要点，长文用段级引索定位到段、只取那一段，深层原文（当时的思考、命令、结论）留在本地向量库里按需取回。检索自带噪音过滤与时间通道，零联网（本地嵌入模型），不改动官方内核。

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

Web-novel writing assistant preset for DeepSeek Harness: the main agent acts as editor-in-chief and delegates outlining, drafting, review, lore-keeping and research to five helpers across a seven-phase workflow, with the whole novel kept as a structured markdown/YAML novel/ directory (character cards, a foreshadowing state machine, timeline, narrative memory), plus a sidebar creator panel and six zero-dependency CLI commands.

Long-term memory for DeepSeek Harness: multi-channel retrieval and an evolving memory store.

Bridges the MemOS memory service over MCP: the agent gets add/search/update/delete memory, multi-cube sharing, and a memory scheduler as mcp__memos__* tools.

Long-term memory for DSH: conversations auto-distilled into atomic facts, scene summaries and a persona profile, with relevant memories injected before every model step. Zero-config out of the box — hybrid BM25 + vector retrieval, optional offline local embeddings, chat/work family separation.

Knowledge base as a canvas in the right sidebar: notes are nodes, and nine tools let the model read, write, link and remove them. A node can carry pictures and documents, and reading one returns their text — Office files extracted in place — while pictures can be handed over as images.

Windows-only plugin that watches the foreground window title, recognizes Bilibili video courses, classifies them by subject, fetches metadata/danmaku/comments, and generates Markdown + Mermaid knowledge maps and Word study manuals (Word output needs a local Python install).

Local literature knowledge-base RAG: 10 tools (kb_ingest, kb_search, kb_rag, kb_zotero, kb_dedup, kb_clear, kb_fetch, kb_scope, kb_stats, kb_status), hybrid BM25+vector+reranker search, cited QA with clickable DOI links, all-local bge embeddings over a single-file SQLite index. Needs Python 3.9+ with pymupdf, faiss-cpu and sentence-transformers; the `npx dsh-kb-rag-install` installer sets those up and pre-downloads the model.

Semantic retrieval, resource management, auto-recall (user + agent dual spaces) and session memory for DeepSeek Harness: memsearch/memfind/memread/membrowse/memgrep/memglob over viking:// URIs, memadd/memremove resource management, memqueue observer status, memcommit session capture, and memlearn skill playbook minting.

A self-contained second brain for DeepSeek Harness — auto-captures durable dialogue knowledge into a local Markdown vault (custom dedup, CJK search, git-friendly), with a graphical knowledge base and an interactive knowledge graph (legend filter, time-dimension coloring, box-select, merge, delete, PNG export/import).

Memory profile composition with Chinese session search, hybrid recall, persistent workspace facts, user-pinned rules and reusable native skills. Install the standalone versioned Release bundle with one dsh plugin add command. Requires Node.js 24 and pnpm on PATH.

StrataGate gives DeepSeek Harness evolving, local-first long-term memory for user preferences, project decisions, conversations, and tool results across sessions; it layers history with user-tunable time decay, reinforces memories through real answer use, shows workspace-aware usage counts, and keeps recalled evidence traceable to its original messages.

Memory in global and per-project scopes: memories are injected into the system prompt at session start, a settings panel edits them with confirmation on write, and the agent gets a read-only memory_query tool (npm: `dsh-my-memory`).

Cross-session persona and diary for DeepSeek Harness: each turn can leave a first-person diary entry with a short retrieval index, and the next conversation injects the persona, a hand-note file you write yourself, and a dated batch of past entries retrieved by searching the diary text itself; anything older is found through feiyu_recall using that index.

The memory organ of Agent-Body: after 2 minutes of silence it enters light sleep and after 5 minutes deep sleep, where deterministic rules distil real experience into memory cards (pitfalls, playbooks, hotspots, unresolved issues, facts). Incoming commands recall related cards by keyword and inject them into context; cards unused for long decay on a half-life and are archived rather than deleted. It also de-noises body-wide homeostasis warnings: repeats inside a window are counted instead of re-printed, and a warning that keeps recurring without ever healing converges into a known steady-state offset and goes quiet. Consolidation and recall make no model calls.

Automatic context compression for DeepSeek Harness: compresses tool outputs before they reach the model and keeps every lossy compression reversible via CCR retrieval tools.

ShiGuang Memory Engine (SGME) bridge: multi-agent shared long-term memory via HTTP — L0/L1/L1.5/L2 distillation, scenario-based injection, unified search, and proactive care signals (memory_search / wiki_search / signal_pull / signal_claim / signal_ack), installable as `dsh-sgme`.

Wenyuan Pavilion: an AI Team workbench for DSH with owned tasks, independent acceptance, an append-only ledger and concurrent projects. Install it into its own profile (dsh plugin --profile ai-team add @suifei/dsh-ai-team), not web or desktop: its patch sets that profile's sandbox to danger-full-access and approvals to never, and the member agents run with full access. The project's PMO acts automatically by default (every 60 s it resolves pending decisions and wakes owners to dispatch the next tasks); turn off PMO auto to send decisions to your inbox.

All-in-one local memory: JSONL files per scope (session, project, global, or a custom name) with per-scope dedup, five model tools (memory_save, memory_search, memory_list, memory_get, memory_forget), automatic recall and hard rules injected into the agent pre-step, and a settings panel. Retrieval combines lexical IDF with a local embedding backend, which the panel can install and manage itself.

Host-level proactive wake-ups for DeepSeek Harness: the model schedules its own alarms (once, recurring interval, or cron, with optional random jitter), cold sessions are woken on time by session resume, model-initiated follow-ups are gated by quiet hours and a daily delivery budget, silent wake turns end with proactive_reclaim and fold out of model context as tombstones, declared schedule files glob-sync JSON schedules into host alarms idempotently, min_idle_seconds defers wakes until the destination session quiets down, and a web panel (settings section plus per-session tab, SSE live refresh) manages alarms and wake history — the heartbeat engine for AI companions and roleplay characters with their own daily routines and world evolution.

A markdown notes manager for DSH: full **MD notes manager** and **MD notes editor**, quickly capture conversations into notes, maintain notes by **syncing to Git repositories**, and **bring notes into the conversation context**.