Plugins

Two-pane model picker that replaces the composer model menu with a searchable provider-grouped list on the left and a detail card on the right showing the selected model's context window, output cap, capability tags and reasoning-effort levels, all read from that model's own provider. The npm name dsh-model-picker belongs to another author; install through this GitHub source.

Adds mark-unread, copy session info, reveal in Finder or open with your IDE, and permanent delete (with child sessions) to the DSH sidebar session menu, plus error and unread status dots, hover-card details, one-click delete for archived rows, and a settings panel that switches each menu item on or off; the interface is available in English and Chinese.

A context usage ring with configurable character-based automatic compaction, manual compaction, protected user requirements and recoverable original history for DSH 0.2.0-rc.2.

Long-term memory scoped to the DSH workspace. A session opens with a one-line-per-memory index - bodies are fetched on demand by the `memory` tool, so the same character budget holds about three times as many entries - and when a turn ends a purely local search over the last user message pulls the matching memories into the next briefing at no model cost. Optional auto-capture distils a stretch of conversation into structured memories; in draft mode they wait in an approval queue instead of landing directly. A portrait layer keeps a workspace and a global picture, rewritten from the journal and the records, with the same draft-or-direct choice. Settings → Memory holds the archive, list and timeline views, a health check (duplicate clusters, stale entries, broken links), the supersede version chain with rollback, and a read-only scan that imports existing WorkBuddy / Qoder memory files.

Runs the standalone opencode2api backend (jasonxu114514/opencode2api, Windows x64/ARM64, no Docker or OpenCode CLI) with DSH and on exit stops only the process it launched; its settings card installs, updates or rolls back the backend from checksum-verified GitHub releases, copies the initial admin password and syncs /v1/models into an opencode2api provider with context, vision and reasoning efforts, re-syncing every 10 minutes.

Cuts session input tokens three ways, each with its own switch in a panel under the composer: lossless structure-aware compression of tool results on `tools/post-execute`, then a per-tool head/tail elision that always names a recovery path through the shared spill store; tool-catalogue visibility per agent on `agent/created`; and a per-workspace memory document that recall matches against each new message and injects through `agent.inject`, so the transcript is not re-read. Measured 41.76% fewer prompt tokens over 149 recorded requests, with a bundled script that re-measures any profile.

Adds a right-click menu to the DSH web UI for files and for links: a file-tree row, a file path or file mention in a chat message, or a hyperlink opens a menu that previews a file in DSH, opens it in the default application or a chosen associated one, reveals it in the file manager, copies the path, the workspace-relative path, the file name, the link address, the link text or the file contents, saves a copy elsewhere, and opens an HTTP(S) link in the sidebar browser or in the system browser, while a right-click that is not on a file or a link keeps the browser's own menu.

Share an existing OpenClaw Markdown workspace with DeepSeek Harness as bounded persona and memory context, with Sidebar browsing and editing.

An announcement file shared by several agent sessions on one machine. It is a plain text file the agents only append to; before each step a session receives the entries it has not seen yet, a new session catches up on the ones still in effect, and a session whose context was compacted gets them re-sent.

Branch and worktree management for DeepSeek Harness: the workspace toolbar shows the current branch with in-place switching, plus an IDEA-style branch selector, remote branch checkout, context menus (create, rename, delete, copy), push and update, and branch isolation into standalone worktrees with managed creation and deletion.

Browser provider for DeepSeek Harness: hand it a web task — open a page, click, type, fill a form, read what is on it — and it drives a real browser step by step, seeing an indexed table of what can be done on the current page instead of raw HTML or screenshots. Each step is one bundled-Jev decision rather than a full model turn (1.1 s median per step versus 2.8–3.6 s for chat-model turns in the repo benchmark), and the main conversation receives only the conclusion, so its context does not grow with the page. Targets come from the page it just read and a changed page is re-read rather than clicked blind, and it runs in the browser that Session owns, leaving your everyday Chrome untouched unless you switch to attach mode.

Delete one finished turn from a DSH conversation without deleting the session — the trash button next to the last assistant reply removes the question, that reply and the tool records of the turn from the conversation surface and from the model context, while the session id, title, later turns and the append-only log stay; the removal is written as a persistent tombstone, so it survives a reload.

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

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.

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.

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.

Plugin security review for DeepSeek Harness: dependency advisories, contextual static evidence, a call-time gate for high-risk plugins, and reversible review-gated enforcement.

Native DeepSeek Harness plugin: feeds every prompt into the local agent-feedback-loop capture pipeline and injects compiled recurrence rules back as context.

Counts completed compactions per session in a floating window and warns only after repeated compactions plus extra token spend or high context occupancy, with all three thresholds adjustable in Settings.

OpenBKN business knowledge-network context for DeepSeek Harness

DSV4.1 reasoning support with multimodal context and bounded artifact acceptance for DeepSeek Harness