Plugins

Memory-assembly team for DeepSeek Harness: every message triggers a five-step cognition loop (judge, retrieve, assemble, feedback, calibrate) carried by role-playing subagents (judge, retriever, archivist, advocate, editor, scribe), using BM25 retrieval, time-ordered material, and LLM assembly to build useful material packs injected into linghun. Works with dsh-linghun.

Control pnpm build-script approval across DSH profiles from Add Plugin, and repair same-Git-URL updates on DSH 0.2.0-rc.2.

Persists unsent composer attachments per session, so images and files pasted into the input box survive page switches, conversation switches and app restarts: the bytes are mirrored in IndexedDB and handed back through the official createDrafts/addAttachments channel, and are dropped as soon as the message is sent or you remove them.

Adds native Codex OAuth sign-in, main-Agent default model selection, and direct or local-proxy settings for DSH Desktop 0.2.0-rc.2 on Windows.

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各个模型厂商/中转 实时显示账户余额插件

Grounded web search for DeepSeek Harness through OpenRouter-compatible gateways: the built-in web_search tool runs on the same endpoint and key as your chat models, returns citeable sources, and is configurable from the Plugins settings page.

DSH 插件市场：浏览官方与社区插件，装之前先给出兼容性结论，一键交给官方安装管线。Plugin market for DeepSeek Harness: browse official and community DSH plugins with a compatibility verdict, and install them through the official plugin manager.

anagenesis —— DeepSeek Harness 上的可编程记忆编排层 + 自我进化引擎：自带闭环记忆存储（不依赖任何外部记忆插件）、17 个面向 Agent 的语义记忆工具（召回/提交/提升/降级/拆分/锁定/过期/反事实重思）、运行时可切换的注入策略、带审计与回滚的元策略自调节、全程可逆效应、自动注册 `anagenesis` Agent 预设，以及零依赖可视化层（终端仪表盘 + mermaid/d2/ascii 文本图表 + 可选桌面窗口）。

AI-agent-driven automated testing platform for DeepSeek Harness (dsh): drives the harness agent through long-lived multi-round sessions to write and run Markdown test cases, file bug reports, fix the code and re-verify the fix, with a per-project serial queue, a development board and built-in load testing.

Long sessions get expensive, and the platform compacts the context on its own. This plugin adds an occupancy badge (hover to see how it is computed), writes a handover draft into HANDOVER.md from 45% — files changed, money spent, what recent turns were about — and reminds you once at 60% to wrap up. On compaction it records the reading from just before, so you can check it later. No model calls, nothing added to the conversation; it does not prevent compaction.

A persistent multi-step task stack for DeepSeek Harness agents: focus_task / focus_complete / read_focus plus a /focus command, with zero automatic prompt injection

Save whole turns — the question plus the full answer — as plain Markdown inside the session workspace, promote the good ones into a cross-project personal knowledge base, and let the model search it on demand. No database and no runtime dependencies.

Native token-based themes for the DeepSeek Harness Web GUI, with custom colors and system font pickers.

Russian localization for the DeepSeek Harness (dsh) web UI — registers the `ru` language (63 namespaces, 3119 strings)

A project-scoped memory plugin for DSH. Knowledge authoring and the plugin's own prompts are open to editing, so users can redesign the library structure and how the model is driven without changing a line of code. By default the library is built on one core idea: a project document you design yourself (a handoff by default) is the project entity; the plugin detects which project a session belongs to, binds captured knowledge to that project, and promotes what generalizes into theme and global layers. The most natural logic there is does the pre-filtering of knowledge, with controllable compression and archiving of context.

Claude Code-style prompt history, double-Esc picker, selection quote/copy & right-click paste.

DSH plugin: a PosterFlow launcher in the Web sidebar — click 开启生图模式, play a transition video, then open the site.

A chip at the left end of the composer tool row showing whether DeepSeek bills at peak or off-peak right now. Clicking it opens a card with the current state and rate, the next switch with a countdown, and why this instant is in that state: a weekend, a named statutory holiday, a 调休 make-up workday, or simply outside the peak windows. Times are resolved in Beijing time with an explicit UTC offset, so the verdict does not depend on the machine clock; a hard-coded 2026 Chinese holiday table carries the 33 holiday days and the six 调休 workdays, and a year beyond the table says so instead of guessing.

Context fullness bands, the per-session compaction threshold derived from the model window, per-step cost computed from cache read and cache write rates, cache-hit, DeepSeek balance with the peak/off-peak tariff, and a one-click handoff. It never calls a model and spends no tokens.

Manage skills and MCP servers from one DSH settings panel. Skills are read from disk: browse, search, preview the body, create, rename and delete, with a backup written before every removal. Global MCP servers are the real cordis.patch.yml loader rows; per-project entries mount only for sessions in that project. Each expanded card lists the tools that server actually registered, and a per-server allow/deny rule keeps only the ones you need — a blocked tool never enters the tool registry, so it costs no context on every turn. Every MCP card carries a connection status tag (connected with a tool count, retrying, gave up, activation failed) plus a one-click reconnect, so a server that fails at startup is visible instead of silently missing its tools. Imports existing configs from 26 other MCP clients.

Cone crusher selection and crushing-plant design for MACKORN NH/NS single-cylinder hydraulic cone crushers: requirement-form intake, equipment selection, plant configuration, proposal generation, product-size simulation and field-data calibration. 21 tools, 6 skills, an MCP server, no runtime dependencies.

Below 1024px the sidebar collapses to a 44px floating square and expands into a 280px overlay drawer; picking a session collapses it again and the focus grab that would raise the soft keyboard after a session switch is suppressed.

DeepSeek Harness plugin: tells the model its real, host-measured context occupancy every turn — and keeps compaction summaries from carrying false "context is nearly exhausted" claims.