Плагины

Manages multiple Jenkins servers and triggers jobs from a Settings page, model tools, or a per-workspace "Run Jenkins Job" entry, with a bilingual host + browser UI.

Expands #tag shorthand into snippet-library text before messages are sent; multi-library, aliases, variables and recursion guards.

Auto-discovers model listings, pricing and capabilities from OpenAI-compatible API hosts, normalizes them, and emits ready-to-use model configs for dsh.

Doctrove: versioned library documentation retrieval MCP server for coding agents — catalog lookup, version selection and focus-ranked doc extraction, with zero runtime dependencies and a dsh bundle.

Desktop (native) control for dsh as a stdio JSON-RPC bridge over a Python core: capture the screen, inject pointer/keyboard input, drive accessibility-tree actions, and gate high-risk operations behind required confirmations.

Scans a project's declared build commands — Makefile targets, package.json scripts, just recipes, deno tasks — and exposes them as ready-to-run agent tools.

Slash-command console for dsh: /web start|stop|restart|status, /tunnel SSH forward management, one-shot /ask, and a console TUI launcher.

Persistent model tool-call trace recorder: every tool call is durably written to a JSONL file that survives restarts, queryable via a structured call_trace tool and a callTraceHistory service, with size rotation and an optional floating canvas UI add-on.

Headless Claude Code consultations with advisor, reviewer, and designer roles, returned as reference answers.

SSH/SFTP remote sites and workspaces: manage connections and remote directories like local workspaces.

Content workshop tools for DSH — topic, title, post and content-calendar generation through the built-in LLM.

OpenAI-compatible image generation in DSH Desktop chat: generate inline, edit reference images or chain-edit previous results directly (image-to-image) without re-uploading, with storage cleanup.

Turns markdown into a WeChat Official Account (微信公众号) draft: inlines every CSS rule onto its element because the editor discards `<style>` blocks and class names, uploads each local image through WeChat's own endpoint so it is not filtered out, and creates the draft; it never broadcasts.

Connects DeepSeek Harness to AsimovBox for creating, updating, rendering, and finishing videos through API-key-authenticated tools.

Local-life toolkit for DSH agents: budget planning, bill splitting, unit-price and discount math, common unit conversions (jin/li/chi, C/F, L/gallon), and trip checklists.

Education toolkit for DSH agents: lesson-plan skeletons by grade band, quiz scaffolding and answer-key validation, analytic rubrics, Anki/markdown flashcards, and readability levels.

Academic writing toolkit for DSH agents: paper outlines, title and abstract skeletons, GB/T 7714 / APA / MLA citations, phrasing QA, and a pre-submission checklist.

Notion connector for DeepSeek Harness: search, read, query, create, update, and append Notion pages and databases via six agent tools, with a Web settings page — configured once with an Integration Token.

Write notes and memos to flomo (浮墨笔记) from any agent via the flomo_send tool, configured once with the flomo API URL or API Key.

Auto-supplement QMD semantic search when the model greps/globs a knowledge-base directory: zero-dependency DSH plugin, async injection via next-step, no manual invocation.

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).

PLUR memory rendered into the system prompt on each assembly rather than exposed as a tool call, so the block is replaced instead of appended and context stays flat across a session. Fully local hybrid search (BM25 + BGE fused with RRF), plain YAML storage you can edit, per-workspace scoping, and a /plur-memory browser.

Agent tools for a self-hosted mem0 server: add, search, get, update, delete, history, reset and status memories, with a settings-panel configuration card.

LLM-driven remember/forget memory: after each turn a model decides what to keep (MemoryDirector), injects relevant memories before each step, dedups, and persists cross-session.