Plugins

OpenViking memory and context bundle for DeepSeek Harness: pre-step auto-recall and profile injection, session capture, `viking://` URI guarding, and recall/write memory tools backed by an OpenViking server.

Pre-execution guard that blocks destructive Git and filesystem commands and access to secrets such as SSH keys and .env files before a tool call runs.

Give DeepSeek Harness a real office environment. Univer Office Plugin brings spreadsheets, docs, slides, canvases, relational tables, and more into one runtime — with connected data, validation, versioned changes, and isolated worktrees for multi-agent collaboration.

Turns a video (a local file, or a Bilibili/yt-dlp link) into one addressable storyboard grid — numbered cells with exact timestamps, per-cell transcript and an audio envelope on the same timeline — and video_zoom re-reads any window at higher resolution, so a text-only model can look at the video instead of reading a summary.

Lets a text-only agent watch a live screen or camera feed: every frame is scored by how much the picture changed, only the ones that matter are packed into one numbered sheet with an audio envelope, so the model looks at what actually changed instead of a screenshot every few seconds.

GitHub-topic-driven plugin & skill marketplace: a Settings page that browses the auto-collected registry (the whole dsh-plugin topic plus the skills index, CI-refreshed every 2 hours) with one-click install, type detection, install-script and host-shadow-dependency safety confirmations, env-key management, and the STANDARD.md recognition spec.

Framework-upgrade safety and plugin gating for DSH: a pre-upgrade session-format contract preflight that adapts incompatible plugins and agent presets before you upgrade, automatic rollback on failure, auto-quarantine of plugins that broke a boot, plus environment fingerprinting and a public contract-rule pack. The built-in multi-source marketplace is a discovery layer only.

Paste a link; the agent reads it. Xiaohongshu, Douyin, Bilibili, WeChat, articles, PDFs and audio become citable Markdown for a wiki or knowledge base. On 60 turns with vs without: finishes reading 22% -> 92% (+70 points), times out 68% -> 0%, answer quotes a real source fact 23% -> 82% (the A/B is exploratory: different time caps, no human correctness review). On 123 live links 80% came back usable (93% of the pages that answered); an unreachable link reports in 26 s. Codex, Claude Code, DSH.

Runs Midscene on the models already configured in DeepSeek Harness instead of separate third-party API keys: hosts an OpenAI-compatible bridge on 127.0.0.1 (default port 8787, automatically skipping occupied ports) that proxies chat completions, streaming and non-streaming, to the DSH host model layer, so DeepSeek official routing, CodeBuddy, Codex and custom OpenAI/Anthropic endpoints all become available to Midscene agents while credentials stay inside the provider plugins and the bridge never touches them. A `/v1/midscene-env` endpoint generates the four MIDSCENE_MODEL_* environment lines with the model family inferred, and seven built-in skills — browser, desktop, Android, iOS and HarmonyOS automation plus a Vitest E2E skill and a Midscene knowledge reference — appear in the session skill catalog without `npx skills add`. Install from npm with `dsh plugin --profile web add @tnnevol/dsh-midscene`.

MCP server configuration card for the DSH Web GUI: add / edit / enable / disable MCP servers over stdio (local subprocess) or streamable-http (remote), with js: prefixed expressions for env / header values, status badges, and hot-reload on save.

Enables LLM to use a cli environment.

Puts the Markdown documents, source files, images and video that already exist anywhere in the session workspace into the DSH sidebar, ranked by relevance to the current conversation. The default lexical mode matches your recent messages against title, summary and body locally with IDF weighting (BM25) — no model calls, no network, nothing leaves the machine. The list comes from scanning the workspace rather than from a recent-files list, so restarting DSH or opening a new session does not empty it. Results are organised into a three-tier reading order (primary / supporting / related) with a verifiable reason on every row — which field matched, which document cites this one — and one click opens an in-place preview: Markdown as rendered text, relative-path images actually drawn, source code with the host's own syntax highlighting, video streamed over HTTP Range. The same Context Pack is exposed to the agent as a knit_docs tool. Later versions added read evidence and lifecycle tracking (attribution is frozen at the moment of reading), pin / exclude (exclusion applies before retrieval, and is undoable), relation evidence (references / imports / tests, with line numbers) and an incremental index reused across restarts. Since v0.23 there is also an optional hybrid mode: it is off by default and only runs once you configure an Ollama or OpenAI-compatible embedding provider yourself. When it runs, what leaves the machine is your query text plus each candidate file's title and summary — a Markdown summary is an excerpt of the body's first paragraph (at most 60 characters), a code file's summary is its workspace-relative directory, and an image or video contributes its file name; full bodies and absolute paths are not sent, and a loopback provider keeps everything on this machine. Since v0.24 it also associates uncommitted changes: a read-only git status (fixed argv, no shell, whitelisted child-process environment) combined with the same reference / import / test / mention evidence shows which files a change is likely to drag along, and it is off by default. The benefit of semantic retrieval still awaits a real-provider run, so no recall improvement is claimed.

One settings panel managing MCP, skills, memory, subagents, prompts and sessions; customize scene combos to switch the whole environment; the Agent can also operate this plugin for you.

Isolated-environment browser verification skill for DSH plugin development: a throwaway DSH_HOME, its own `verify_<random>` profile, its own port and its own browser instance in one command, cleaned up on exit, so the profile you are actually using is never touched; ships a zero-dependency raw-CDP driver (snapshot / click / screenshot / eval) and an optional isolation audit.

Right-side details panel that turns the Matt Pocock skills collection into a DSH quest board: wayfinder decision maps, per-issue triage / fix / discuss / execute actions, 9-item core-skill probe plus 20-skill radar, environment checks, and one-click handoff across sessions.

MCP server manager (stdio / streamable-http): per-working-directory project and global config tiers; project-level MCP collapsed into 4 atomic tools through a middleware layer by default (`middleware: all` folds in global servers too, hot-switchable in the settings page); workspace isolation prevents cross-project interference; configs keep `${ENV}` references only, with no plaintext secrets on disk; runtime registration API for other plugins to inject MCP servers.

Image generation and image reading for DSH: a 创作 sidebar page (one row per model, 10 ratios, 1K–4K sizes, a contact sheet with detail cards, zoom, reuse and delete), three preset providers plus custom endpoints — one needs no key at all — and a vision-review skill. A pasted key is written to ~/.dsh/secrets/media-tools.env (mode 600) and only sent to the provider you picked. Requires Python 3.9+ (generation runs through scripts/generate.py); the 创作 page needs desktop DSH 0.2.1+.

Git worktree Session Targets with isolated task sessions, Ready for Review, reversible Local Preview, human-confirmed delivery, environment retention and recovery, and same-session iteration.

Smart Charts skill: turns CSV/TSV/TXT/XLSX/XLS/JSON data files into standalone interactive ECharts HTML - 32 chart types including offline maps, 3 themes, no CDN. A --profile data profile (per-column dtype, cardinality, missingness, samples, statistics, entity grain, insight signals) lets the agent read the data and pick the chart itself; each chart embeds a fact sheet (plot_stats + data_preview) whose numbers are the only quotable values. LLM transform code runs in a restricted sandbox (blacklist + AST whitelist + safe builtins); --doctor self-checks the Python environment. Fully offline, ECharts bundled.

Semantic retrieval, resource management, auto-recall (user + agent dual spaces) and session memory for DeepSeek Harness: memsearch/memfind/memread/membrowse/memgrep/memglob over viking:// URIs, memadd/memremove resource management, memqueue observer status, memcommit session capture, and memlearn skill playbook minting.

Analyze Windows disk usage, compare scans, and manage cache cleanup and developer environment migration in DSH Web.

Bridge Claude Code's .claude/ directories into DSH with zero migration: project and user-level skills, commands, rules (one system-reminder envelope), agent files, hooks (PreToolUse/PostToolUse/UserPromptSubmit/ SessionStart/SessionEnd) and .mcp.json servers, plus Claude Code plugin marketplaces. Ships /cc-plugin for full plugin/marketplace management (claude CLI first, self-implemented fallback), /cc-resume to list and import Claude Code sessions into DSH as native event-sourced logs, and /cc-export to write DSH skills back as Claude Code skills. Two-way Claude Code <-> DSH bridge, versioned and released as dsh-claude-compat.

Low-cost video understanding tool: a video_understand tool turns a Bilibili link / BV / local video into an AVIS info layer (ASR + scene structure + object tracks + YOLO labels) and returns summary + Q&A. Question-driven dynamic routing across layers (L0 ASR / L1 object tracks / L2 key-frame VLM), semantic-layer reuse for repeat questions, per-question budget cap. Python engine: core layer needs faster-whisper / opencv / yt-dlp (~200-300MB); the optional semantic layer adds ~2GB of torch / transformers / ultralytics. A bundled doctor --fix sets up the venv and installs both.

Reads Harness replies aloud through an existing local TTS runtime: built-in IndexTTS and GPT-SoVITS launchers, a protocol-based local HTTP/JSONL entry, and model-folder loading for Kokoro, F5-TTS, VoxCPM, Qwen3-TTS and CosyVoice SDK environments. Ships no models. Derived from 1624318455/dsh-plugin-tts; it isolates its row id and settings, so both can be installed side by side with duplicate features deactivated.