Plugins

Canonical project memory for DeepSeek Harness: one governing article per asset, an append-only journal beneath it.

DSH knowledge-graph memory with a better-sidebar tab and a standalone /graph-memory/app dashboard: extracts TASK/SKILL/EVENT nodes, recalls across sessions, and ships as the npm package dsh-graphmemory.

DeepSeek Harness (Cordis) plugin — bi-temporal VSA memory + cognition engine + BLAKE3 provenance, exposed as a DSH storage+session plugin. End-to-end tested with a real Python subprocess.

Git-native, auditable long-term memory for AI agents

Cross-app project memory for DeepSeek Harness with role-separated writeback, a visual knowledge workspace, confirmed corrections, session controls, local Writer and organizer settings, and an account-free Windows local installation preview.

DeepSeek Harness memory and knowledge hub that routes update, retrieve, and subscribe calls across compatible plugins, with an optional transactional Rust backend.

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。

Project memory for coding agents on DeepSeek Harness: similar past edits surface as precedents, out-of-scope edits are blocked, and cognition persists across sessions (47 upstream-verified fixes, gold-free 20-task run).

Cross-session event-cue memory for DeepSeek Harness: auto-extracts task/conversation cues and user language habits from every turn into a persistent global cue bank, then re-injects remembered context on topic-switch detection (keyword or vector matching).

Local Markdown wiki as long-term memory for DeepSeek Harness — ported from llmwiki

Cited memory over DSH's lossless session log: distilled facts carry `(sessionId, eventRange)` citations that expand back to the exact original log excerpt.

Experience and skill engine with a sidebar console and exp_record / exp_recall / exp_feedback / exp_consolidate / exp_type tools, stored in a local JSON file. Optional Git backup (off until you configure a remote) pushes the library to a remote you choose; GitHub sign-in uses a device code or a token kept in local settings.

Structural scaffolding for DSH agent continuity: layered memory (hot/index/judgments), judgment cards, handoff packs (compact mode), compaction review. Zero-dependency, pure files, portable — rebuild the 'self' across model changes. Not a memory engine; the skeleton of continuity.

Three-tier memory (personal, project, session) built on the Hy-Memory engine, with relevant memories injected before each step. Ships seven memory tools (search, add, list, get, update, delete, forget), a settings panel with per-tier lists, editing, change history and duplicate cleanup, real token accounting per write, session summaries written by the engine at session end, and a user profile refreshed from recent memories. Memories can be exported to and imported from MemHub. Needs Python 3.11+ once to install the engine, or uv, which fetches 3.12 itself; uninstalling keeps the stored memories.

Cross-session long-term memory for DSH: eight memory layers, four notebooks, hybrid SQLite FTS5/vector/graph retrieval, agent-driven automatic capture, write lifecycle hooks, optional write audit, project spaces, forgetting and a visual management page. Full FTS5/vector/graph retrieval needs the bundled Go service, which ships only as a Windows x64 prebuilt; on macOS/Linux, build it from source or the plugin falls back to Node SQLite without FTS5 and retrieval degrades.

A cross-workspace Library for DeepSeek Harness: agents record files, tools, environments, knowledge and work records so any later session can index, search and reuse them.

Hy-Memory 2.0 as a native DeepSeek Harness memory component: three-tier memory (personal / project / session), three scenes (chat / working / coding), automatic recall and capture with tool traces, a Settings > Memory panel, and MemHub interoperability.

Layered memory for AI agents: five verbs (wake/work/pit/tomb/close), core layer read every time, archive on demand. Plain markdown, four pages created on first run; survives restarts, model swaps and plugin removal.

Diary and narrative memory for companion agents: daily first-person entries scoped per group or private chat, refs that can be checked against that day's messages, and a read-only journal page where hand-drawn doodles and photos follow the sentences they belong to.

A durable RAG-enhanced long-term memory layer for LLM agents, featuring holographic memory, state-slot conflict detection, and timeline retrieval. Requires Python 3.10+ and this repository's Python dependencies: create a venv and run pip install -e ".\[dev]" in the checkout before enabling the plugin (the bundled installer is a PowerShell script, i.e. Windows).

A persona that grows from experience: remembers what happened, becomes someone from it.

人格 + 情感 + 记忆的 DeepSeek Harness 插件：把「一个会记得你的角色」接进 DSH。

Long-term notes and daily journals kept per workspace in a hot/cold archive, each tier with its own index and rebalanced once a day; read and written through seven memory_* tools, with a settings page for per-workspace options.

Cross-session long-term memory for DeepSeek Harness: pinned rules injected every turn, the rest recalled by IDF-weighted keyword evidence, fact-key dedup, plain JSON storage, and a settings page to edit or delete entries.