Plugins

Bridges session images to configurable vision providers and returns text-only analysis to eligible DeepSeek Harness model routes.

Per-workspace completion ringtones plus attention sounds for approval, question, plan-review, goal-blocked, and task-failure events, with built-in synth, voice (TTS), and custom audio.

Draggable grid-aligned workbench of 28 mini-cards in the margins of the conversation (API balance, token usage, cost, context pressure, todos, goal, usage heatmap, GitHub repo, image relay), with S/M/L/XL size tiers.

DeepSeek account balance and per-session cost card in the sidebar foot.

DeepSeek API spend (current session and all sessions) and account balance in the aside panel, with official pricing and peak/off-peak support.

Pairs two DeepSeek Harness machines with a one-time code - directly on a LAN, or across networks through an end-to-end-encrypted relay with a zero-config official default - so one agent can run tasks and exchange files on the other while each machine keeps its own files in place.

A judgment core for DeepSeek Harness: a cognition loop that gives every decision a source and attribution and drives planning to a close, hippocampus memory that condenses running experience into reusable knowledge, and a customizable persona card (name, personality, communication style). Requires DSH ^0.1.0-rc.7.

Persona engine for DeepSeek Harness: one config.json drives the AI's self-name (per model, per tier), how it addresses you, relationship stance, character text, per-item work contracts with individual toggles, thinking-chain language, appearance and reply tone (both opt-in and per-model overridable), and long-term memory gated by human confirmation - the AI can only append proposed candidates, a human confirm line flips them into effect, and the log is physically append-only and replayable. Confirmed entries are injected as a quoted data-not-instructions block; entries tagged with a kind can instead be routed to arbitrary files on confirmation and never reach the prompt. Three prompt sections re-evaluate from disk on every assembly, so edits apply on the next step with no restart. Persona presets are shareable JSON snapshots (imports and exports SillyTavern character cards, v2/v3 read, v2 written) and deliberately never carry memory. Zero runtime dependencies, no network, no shell; any error degrades to an empty section rather than a broken session. Ships blank - installing changes nothing until you write something.

Model switching and reasoning-effort control for DeepSeek Harness: set_model and list_models agent tools let the agent autonomously change its provider, model or thinking depth (reasoning effort) mid-task with a mandatory reason, a provider whitelist and a context-window token-pressure guard, the active model is injected into the runtime context, and Plan Mode auto-transition switches to a configured planning model on entering plan mode and restores the previous execution model on exit.

Persistent Endeavour and Challenger peer sessions for DeepSeek Harness that plan, execute sequential tasks, and verify reported results.

Feishu/Lark gateway for DeepSeek Harness with topic-persistent conversations, live execution cards, image and file inputs, in-chat approvals and questions, source allowlists, and durable one-time or recurring agent tasks created in natural language.

Sign in to DeepSeek Harness with a Claude Pro/Max membership (no API key), downscale Anthropic request images to a 2000px long edge, slim /compact summarizer payloads, and show 5-hour/weekly plan usage plus DSH message counts.

Plan-usage pet for the DSH web GUI: a floating skeletal-animated character reports quota in a speech bubble, auto-matching the configured provider (OpenCode Go, Command Code, DeepSeek) to show a plan percentage or an account balance, and falling back to local token stats when the provider API is unavailable; draggable, wheel-scalable (90-260px), synthesized click sounds, loopback-only routes.

One-handed, keyboard-free input for the composer: press and hold the mouse on the input box, speak, release — the text lands in the draft, and sliding up cancels without leaving a half sentence behind. No mic button to aim at and no shortcut to remember; the hand never has to leave the input area, which is the point when the other hand is busy. Recognition runs fully offline (SenseVoice via sherpa-onnx, no API key, audio never leaves the machine).

Pairs the running executor with a stronger reviewer model through zero-parameter advisor() calls and step-based patrol checks, returning plan, correction, or stop guidance.

Zero-config lint feedback loop for JS/TS, Python, Go and Rust: lint_diagnostics / lint_workspace_errors / lint_fix tools driven by the repo's own eslint / biome / ruff / golangci-lint / cargo clippy (auto-detected from config files, repo-local node_modules/.bin resolved first, nothing bundled), plus an auto-injected post-edit findings delta on the harness fs/observed event and a bounded completion gate — edit → lint → auto-repair with one lint_fix call for dsh agents.

Cherry Studio-style paste: multi-line/indented/fenced text or code pasted into the DSH Web composer collapses into a bordered, collapsible, language-tagged card and is restored as a fenced code block on send.

Multi-machine, multi-agent orchestration and control plane for DSH: discovers Agents and workspaces across devices, routes tasks by machine, repository, capability, and load to local or remote Agent runtimes, streams progress and results, forwards approvals, and recovers durable tasks after disconnections.

Plays a chime and speaks a Chinese voice alert when an approval, question, or plan-review popup appears in the DSH web GUI, so you never miss a request.

TypeScript and JavaScript LSP configuration plugin for DeepSeek Harness using typescript-language-server.

Swift LSP configuration plugin for DeepSeek Harness using sourcekit-lsp.

Rust LSP configuration plugin for DeepSeek Harness using rust-analyzer.

Ruby LSP configuration plugin for DeepSeek Harness using ruby-lsp.

Python LSP configuration plugin for DeepSeek Harness using Pyright.