Plugins

A memory plugin for DeepSeek Harness: set its name, personality and character; it forgets only trivial things, keeps what matters, and marks and remembers what is special to you.

Gives a DSH agent five layers of persistent memory kept as plain Markdown files — persona, speaking-style rules, daily diary, session archive and open loops — rebuilds a system-prompt section from them within a minute of a file change, and adds three tools (memory_read, memory_write, memory_search) plus an importer for migrating an existing memory directory.

Persistent persona memory for DSH with a unified recent, long-term and archive timeline, bounded context loading, memory retrieval and isolated task delegation.

Improves conversation drafts with optional conversation, memory and project context, side-by-side previews, a dedicated model and one-step restore; never sends messages automatically.

Opens a temporary side conversation in the right Sidebar that reuses the host conversation UI, so answers render with the same markdown, tool steps, timing and token usage as the main thread. Selecting part of an answer opens that conversation side chat with the passage quoted: the quote waits as a pill inside the composer, rides along with the next message, and joins the side chat context. The side chat runs on its own memory-only session: the parent snapshot is reference context only, and nothing is written to the session log.

DeepSeek Harness (DSH) plugin: an Overview tab beside Chat/Trajectory plus a right-sidebar page summarizing session progress (goal, todos, key steps), artifacts, and references, with per-turn scoping, OpenViking memory preview, and quick-nav linkage.

DeepSeek Harness read-only companion for dsh-cost-meter: a sidebar row that splits today's cost per provider:model, hovering for the full breakdown. Reads the main plugin's in-memory statistics when available so numbers track it exactly; never writes the

Codex-style file-based long-term memory for DSH: two-stage LLM extraction, consolidated MEMORY.md handbook, prompt-injected memory summary, and search/read/list/note tools.

Firecrawl as the DeepSeek Harness web backend: query routing, on-demand enrichment, credit budgets and failure memory for web_search/web_fetch.

The 7-7-7 execution loop for DeepSeek Harness — plan, run, capture, close, compound, with a human gate.

全局记忆：AI 主动写入与读取的记忆文件，每轮对话前自动注入索引，不占上下文，仅按需展开；支持本对话禁用。

Native shodh-memory integration for DeepSeek Harness — persistent cognitive memory without an MCP server in the context window.

In-app server monitor window for DSH that tunnels to a lightweight agent on your server: memory, swap, load, disk, per-container usage and QQ status, cache purge and container restarts, plus an embedded VNC desktop for manual QQ QR login and sign-out. The agent ships in the repository (server/monitor.py) and you deploy it yourself.

Local-only memory guard for the DeepSeek Harness: host heap and session-log monitoring, oversized tool-argument interception, and dry-run by default session vacuum.

Windows commit-charge watchdog for DSH Desktop: samples committed memory every 5 seconds, attributes it to the DSH process tree and the largest consumers, blocks automatic restart when DSH is not the main committer, and adds read-only pagefile advice, a 7-day crash timeline and an event export; automatic restart and crash resume are both off by default.

Per-workspace memory library with manual per-chat opt-in, editable rules, three sharing modes, and continuous forgetting; cards stay readable Markdown.

Distills long sessions into background observations and reflections, injects them as a system-prompt section, and renders compaction summaries from prepared memory; includes a Settings page and source-backed recall.

DSH Web 插件：对话顶栏 / 输入框底部 / 侧栏底部显示本机 CPU、内存、磁盘、网络、I/O、温度，点开右侧「系统」详情

给 DSH 上的一个会话装上自己的目标、记忆和作息：goal / memory / clock 三个插件

A small living fish with its own memory, mood and quiet thoughts. It remembers you between sessions, and the fish itself is one JSON file you can export and carry.

Cross-session memory for DSH: export every session to readable Markdown transcripts, keep one long-term MEMORY.md, and get a wake-up summary in a fresh window.

Port of the V2 memory pipeline from OpenAI Codex to DeepSeek Harness: a background agent extracts each idle session, consolidation folds the extractions into one memory_summary.md behind a git baseline diff, new sessions get that summary injected, and cited memory flows back as usage counts. A Settings page chooses the model, each stage's reasoning effort, and the idle, age, concurrency and timeout limits.

Send "Memory unlocked" to let the AI recall conversations it has forgotten.

Three-layer memory for DeepSeek Harness — a small always-on core block plus on-demand topic files (profile, preferences, decisions, lessons), with source-annotated writes and supersede-not-overwrite history, so preferences and project constraints stop drifting between sessions. Local-first: no vector DB, no server, no outbound calls.