Plugins

Ollama provider for DeepSeek Harness with model management, health checks, rule-based local routing, and cloud fallback.

Connects DSH Web and qq-bridge to OFM, defaulting to the DeepSeek public pool while preserving reasoning effort and manual model selection; loads the official OFM dependency when absent and reports account-rotation receipts.

Seven agent-preset modes for DeepSeek Harness, each with a fixed tool boundary, per-mode model routing and fast/deep omd_task delegation tiers, plus a plan-to-execute loop (/mode, /start-work, goal-backed /ulw) and a settings page that remaps models per mode and per tier.

Pins every request to the native max-effort tier and adds a per-model/per-mode reasoning-depth panel with a 0-20 capability slider, isolated Velocity/Apex profiles, and offline reasoning toolboxes. Distributed as an obfuscated build; commercial use allowed, reverse engineering closed.

Independent workspace and conversation personas with adaptive styles, approved communication preferences and role-based routing to registered DSH models, including models supplied by Codex and Claude Code provider plugins.

kimi-tide（月汐）— preset-and-rule model router for DeepSeek Harness（预设+规则驱动的逐步模型路由）：named presets with ordered image/keyword-group rules route each agent step across ANY mounted provider/model (candidate pool = full host catalog enumeration, no whitelist), w

Per-step model router: named presets with ordered image/keyword-group rules route each agent step across every mounted provider and model, adding collaboration flows for image transcription, an image guard, a multi-plan quota panel, and per-step decision observability.

Smart subagent routing and evolution: bind roles to any provider/model registered in DSH, including models supplied by Codex and Claude Code provider plugins, with workspace learning.

Named subagent presets bound to model-route allowlists, where an out-of-list child model is refused before a delegation starts and each child conversation shows the model its last request actually used.

Mistral subscription for DeepSeek Harness: model route, multi-account failover, and a composer usage panel.

DeepSeek Harness 多模型路由插件：让专业的事情交给专业的 agent——自定义视觉/翻译/语音/子代理等专业 agent 并绑定独立模型，多模态账号一键登录、账号池健康路由与实时用量统计

Picks each subagent model from the local catalog by task category, unless the caller already named one. Free and quota tiers are ranked together by per-model capability tags; a pricier model is used only when no cheap model is tagged as good at that kind of work. Only providers whose remaining balance is readable, or that are account-backed, enter the candidate pool; the rest stay listed but are not routed. A panel adds per-model manual priority above the automatic order plus allow/revoke controls.

Picks each subagent model from the local catalog by task category, unless the caller already named one. Free and quota tiers are ranked together by per-model capability tags; a pricier model is used only when no cheap model is tagged as good at that kind of work. Only providers whose remaining balance is readable, or that are account-backed, enter the candidate pool; the rest stay listed but are not routed. A panel adds per-model manual priority above the automatic order plus allow/revoke controls.

Use Jev to adjust main-chat reasoning effort without switching its model, independently select and apply fresh sub-agent capability and effort, and inspect decisions with per-reply allocation feedback.

Adds a Settings page to pin one OpenAI-compatible subagent model (or follow the main model), writes the official subagent-model-selection allowlist, reminds the parent to pass that route, and optionally runs one-shot tasks through an isolated Pi CLI provider.

Quota takeover for DeepSeek Harness on top of Our Free Model: compiles your platform order and pinned model tiers into one ordered fallback chain, skipping platforms that lack the model, sit in cooldown or are out of quota, writes the result back as Our Free Model combos, and after a quota or rate-limit failure re-plans and injects a follow-up continue message into the interrupted session so the turn resumes on the next platform; the chain ends with your configured aggregate fallback model or the official DeepSeek quota.

Routes subagent delegations once at spawn time by keyword rules over the delegation label and prompt: the first matching rule sets the child's provider/model/reasoningEffort, explicit caller routes are kept unless a rule opts in, and unmatched delegations pass through unchanged.

官方 subagent 的默认策略包：装上一次配好「什么时候自己干、什么时候派出去、派给谁」。

Named roles, model route guards, native configuration, and request-model visibility for official DeepSeek Harness subagents.

Forensic analysis of past model-routing decisions. Replays each session, classifies every turn's task complexity from its request shape (deterministic, no LLM), and reports two kinds of waste: an expensive model on cheap work (the difference is measurable), and a cheap model on expensive work that failed on its own merits — where every retry re-sends the whole context, so the downgrade cost more than the upgrade. Distinguishes provider-capacity retries (RATE_LIMIT/TIMEOUT/TRANSPORT) from model failures so it does not cry wolf. Derives routing rules from the evidence, priced against a built-in per-million table.

Ranks the models a DeepSeek Harness install already discovered by measured connectivity and speed, and switches to the next candidate inside the same turn when the one in use fails without producing any output. Ships a settings page with a grouped model list, per-model and per-channel switches, and a quota-aware cooldown that rests an exhausted model until the next day.

Routes outbound model traffic per provider host or per model ID through chosen proxies, loopback or direct, configured from a Plugins settings page.

Derivative of dingminhua/dsh-subagent-default-model (do not install both): routes subagent delegations by role with candidate pools, cross-provider failover and fork window slicing; shows running subagents in a header panel with duration and token counts; supports mid-run and batch model switching and exposes routing tools the model can call. Subagent pages also carry a context / usage stats strip (context occupancy, output speed, cache hit rate, token buckets) and a model menu limited to that page’s whitelist — a pick outside the whitelist is substituted with an allowed model instead of running unlisted.

Pick the model your subagents run on — with a reasoning-effort ceiling and an output-token cap — enforced in code on every child DSH starts, whichever tool starts it.