Plugins

A cozy offline vocabulary trainer for the whole family: 1094 curated words, spaced repetition, 6 quiz types, spelling games and a lazy large-screen mode; opens as a sidebar panel and also runs standalone as one HTML file.

Pokemon-style catch-em-all: your real work is the tall grass — turns, tool calls and errors spawn wild encounters; throw balls, fill a 28-slot dex, walk a team of six. Zero tokens, invisible to the model.

A draggable mascot invites you to play Xiangqi (Chinese chess) while the AI thinks, with a built-in engine, move-record export, and optional multi-model commentary.

Dynamic Schulte grid waiting-time mini-game: click 1..N in order on a static grid or a spinning roulette wheel while the model thinks.

Pull a 3D lever next to the send button and turn the model's reasoning signals into a pixel-art gacha reveal.

Runtime security gate on the tool pipeline: denies calls naming hosts outside an egress allowlist, redacts credentials from results at the canonical value rather than only the rendered content, and appends every decision to a JSONL audit log; ships in monitor-only mode.

Complement to official Creator mode: stage, validate, live-mount via ctx.plugin, score, and solidify or roll back in-memory tool-plugin trials.

Model-driven /init command: the agent analyzes the current repo and generates/updates a high-signal AGENTS.md, with a persistent system-prompt reminder to keep it maintained.

Hands standalone jobs to the Cursor CLI signed in on the same machine, with child-model settings and a read-only connectivity test.

Metadata-first runtime profiler for DSH agents: turn/step traces, model and tool wall-time timelines, provider usage, retries, errors, and live or historical sessions.

Read-only health clinic for the installed DSH plugin set: loader health, dependency integrity, version compatibility, install-script risk, duplicates and patch integrity, delivered as a model tool, a Settings dashboard and JSON reports.

One-click launcher for the Web UI: a double-click Start-DSH-Web.cmd on the Windows desktop that boots dsh web and auto-opens the browser (polling until ready), plus a web_launcher model tool (install / open / status).

Minimal prompt x full PTC tools: one-line persona, Code Mode SDK, subagents, workflows, web search, and Windows Git Bash.

Turns the iterate skill into an autonomous closed-loop harness — plan, parallel review, atomic fixes, validate, loop, auto-stop — plus a dry-run review-only mode and a meta-review that audits the report and emits a final review report.

Speech-to-text voice input for the web UI: a mic button in the composer transcribes speech into the draft via the browser Web Speech API (zero-config) or an OpenAI-compatible Whisper API (OpenAI / Groq), with a selectable model and language in Settings.

Chat image-attachment bridge with a `view_image` tool for any OpenAI-compatible VLM (local Ollama or cloud): pasted/dropped images become `view_image` path markers before reaching text-only DeepSeek models.

`describe_image` tool: a vision bridge that sends images to mimo-v2.5 through the opencode Zen API (credential `OPENCODE_GO_API_KEY`, free route first with paid fallback) and returns text descriptions for text-only models, with native passthrough and ImageMagick transcoding of SVG/TIFF/HEIC formats.

Adds an image_describe tool backed by the DashScope OpenAI-compatible vision API; on text-only sessions, pasted images are stored as local paths for the model and rendered inline in the chat transcript.

Agent-callable vision tool that describes local images via any OpenAI-compatible vision endpoint you configure, with an optional multi-model cross-check and no built-in keys.

Auto-discovery vision bridge for text-only DeepSeek Harness agents: automatically finds an image-capable model from your configured providers and returns picture descriptions as plain text via a vision tool.

On-demand vision for text-only DeepSeek models: upload images, and the model calls a view_image tool backed by any OpenAI-compatible vision endpoint (Qwen/DashScope by default).

Vision plugin for text-only DeepSeek Harness models: native image paste, layered evidence memory and cache, and intent-driven tool selection.

Synesthesia Encoder for DSH: a vision model translates images into compact structured spatial text (canvas/elements/percentage coordinates), giving text-only LLMs pixel-level image understanding via the `mm_vision` tool.

Reuses DeepSeek web's built-in vision mode for text-only models: the deepseek_vision tool drives the local deepseek-vision-cli browser automation (manual login helper, deep-think enabled, auto-closes browser) and returns image descriptions as text.