Plugins

DeepSeek Harness plugin that turns Jev judgments into three automatic actions — pruning oversized tool output to the segments relevant to the request, screening fetched pages for instructions aimed at the model, and picking which skill fits the next step — plus the jev_ask and jev_gate tools, a judgment ledger that survives restarts, and a /jev-status report. Needs a TypeSafe API key; without one it is inert and sends nothing.

Early-stage plugin connecting DeepSeek Harness to a separately deployed, self-hosted OwnDsh server for team identity, model access control, quotas, and usage auditing.

Visual round-table meetings for DeepSeek Harness — expert nodes on a ring with directed edges, an aggregation gateway, proxy thinking for black-box worker models, and adversarial review (red-team) of settled plans with per-viewpoint endorse/reject.

"Single-Core Writing" plugin for DeepSeek Harness: Thoroughly tool-streamlined and output-hardened for quantized small models, suitable for running long-novel pipelines locally with on-device models.

DeepSeek Harness universal preset enhancement plugin: an editable preset editor (system/user/assistant entries + camouflage model output prepopulation)

Per-round thinking-level (reasoning_effort) control for DeepSeek Harness: pick Auto and it schedules low/high/max from the recent tool-call history, or fix a wire level (off/on/minimal/low/medium/high/xhigh/max) manually, with custom wire mapping, a model-aware capability guard, and context-window presets (64K–1M); its per-model capability card pairs with a separate plugin, [dsh-llm-openai-completions](https://github.com/drscrewdriver/dsh-llm-openai-completions) (installable from dsh-market), so custom OpenAI-compatible gateways (vLLM / LM Studio / self-hosted) can try reasoning — the card writes llm-pi-ai capabilities, the adapter drives the wire (compat.thinkingFormat), and this plugin auto-maintains the takeover list.

Use a ChatGPT/Codex subscription in DeepSeek Harness with GPT models, image generation, web search, subscription quota reporting, model and feature controls, and browser or device-code OAuth sign-in.

Reads animated GIF and WebP as animations: a pasted one keeps playing in the UI while the model gets a labelled sheet of frames sampled across it, and the read_animation tool samples a file on demand.

Signs in to a ChatGPT account over OAuth and serves that plan's models as a DeepSeek Harness provider route, calling api.openai.com/v1/responses with the account's plan scope rather than the Codex backend.

Merge every locally signed-in WorkBuddy account into DeepSeek Harness as one auto-failing-over model pool (multi-account rotation, live credits, and a model catalog showing per-model credit multipliers and free/night-discount tags).

Computer use through an external USB HID device: name a target in plain language, a vision model locates it in a cropped window screenshot, and a Raspberry Pi Pico 2 moves the real mouse and types on the real keyboard. 7 tools. Windows has window listing, per-window cropping and automatic window raising; macOS needs pyobjc and has neither; Linux is unsupported.

Authentication gateway for the DeepSeek Harness Web UI: the login gate covers pages, /api, /plugins and WebSocket upgrades; PBKDF2 password hashing with per-user salts, HttpOnly SameSite session cookies named per DSH_HOME and IP-based login lockout; invite-code registration; two-factor login with TOTP or passkeys (WebAuthn: several keys per account, phone enrolment by QR, username-less sign-in, and a step-up before any login factor is added or removed); a user-management settings panel (users edit their own profile and manage their own TOTP and passkeys, admins add or remove users, reset passwords, manage invites and clear the passkeys of a lost device); per-user model and API-key configuration whose private entries are encrypted with a key derived from the login password and stay unreadable by any admin, with admin sharing to selected users (usable, balance visible, key never shown, revocation immediate) and unconfigured users blocked rather than falling back to the deployment configuration; per-user isolation on the REST and list APIs and per-frame ownership filtering on the WebSocket mux; session persistence across restarts; a JSONL audit log; and a fail-closed gateway. Requires the DSH 0.2.0 line (the 0.1.1-rc.2 transport line was removed in 0.7.0); passkey login needs a localhost or HTTPS origin because browsers require a secure context.

A whip for DeepSeek V4 Pro: it watches the reasoning fingerprint of every thinking block and pulls the model back when it slips from focused "We will / I will" mode into scattered "let me" mode.

Dedicated model routes, tools, and system guidance for vision, compaction, reviews, subagents, titles, and image generation.

Usage tiers and shareable stats cards: 🐟→🐳 ranks by monthly token burn with a locally-computed estimated percentile, precise pricing for 46 models across 6 vendors (including size-tiered Chinese pricing), backfill of pre-install sessions, and old-vs-new comparison across the 2026-08-17 rate change. Local-only, no telemetry.

Settings page for per-model capabilities: reasoning-effort levels with their wire spellings, input modalities, and token capacities, written as declarations or sparse catalog overrides.

Adds a configurable vision model to text-only main models: a vision_read_image tool, a composer-bar vision-model selector, and automatic image-to-text conversion for text-only routes.

Runtime-switchable model output styles with Claude Code outputStyles parity, plus the output.render.* presentation protocol: a /style command, per-session persistence, systemPrompt injection, six built-in styles, a web picker, and a renderer registry with per-session/per-tool rules and /export.

Codex-style reasoning-effort slider embedded in the model selector.

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.

A novel-writing workbench for DeepSeek Harness: you tap thumbs-up or thumbs-down on candidate passages, and the model distils them into a short preference profile that carries into later drafting calls while the manuscript stays out of the drafting context. Adds a chapter board, per-chapter writing packs, annotation-scoped revision that rewrites only the annotated paragraph and verifies the rest byte-for-byte, a project ledger, and local pacing checks.

Unified anchored agent preset for DeepSeek V4 Pro/Flash on the official API and opencode-go: Minimal-exact two-tool first-request bootstrap, model-aware Pro/Flash paths, and epoch-aware catalog management for long-session stability.

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.

Host-level proactive wake-ups for DeepSeek Harness: the model schedules its own alarms (once, recurring interval, or cron, with optional random jitter), cold sessions are woken on time by session resume, model-initiated follow-ups are gated by quiet hours and a daily delivery budget, silent wake turns end with proactive_reclaim and fold out of model context as tombstones, declared schedule files glob-sync JSON schedules into host alarms idempotently, min_idle_seconds defers wakes until the destination session quiets down, and a web panel (settings section plus per-session tab, SSE live refresh) manages alarms and wake history — the heartbeat engine for AI companions and roleplay characters with their own daily routines and world evolution.