全部插件

DSH / BUNDLE / BUNDLES

dsh-multi-model-orchestrator

v0.2.2Bazley13 / dsh-multi-model-orchestrator65c916a4aa

可安装组合包组合包与其他模块社区 · Topic 自动分析

概览

dsh-multi-model-orchestrator

A DeepSeek Harness (dsh) plugin: orchestrates complex tasks across multiple models — a 'main brain' decomposes the task and dispatches subtasks to GLM / Kimi / Qwen etc. sub-agents by each model's strengths, with per-model token usage.

README / ZH

插件文档

目录摘要

A DeepSeek Harness (dsh) plugin: orchestrates complex tasks across multiple models — a 'main brain' decomposes the task and dispatches subtasks to GLM / Kimi / Qwen etc. sub-agents by each model's strengths, with per-model token usage.

dsh.pub 核对固定版本的组合包契约、运行时事实与分发语义;完整 README 请查看源仓库。

在 GitHub 阅读完整 README

LIMITATIONS

已知限制

- Token usage is **per-process** (cleared when the harness restarts); per-session usage still shows in the built-in token meter. - `model_token_usage` needs at least one model call that returned a `usage` chunk before it reports anything. - The orchestration guidance is injected globally, so sub-agents read it too; its wording keeps sub-agents from recursively re-decomposing their single focused subtask. - Third-party routes are registered as **non-reasoning** models by default; reasoning flags (`reasoningEfforts` / `compat.thinkingFormat`) can be added per model on the web **Models** page. - **Some reasoning models reject a call without an explicit reasoning tier.** Zhipu's GLM-5.3 line, for example, fails with default parameters and only responds when the sub-agent is dispatched with an explicit `reasoning_effort` (e.g. `low`). If a dispatched child errors on a model you expect to work, add an explicit `reasoning_effort` to the dispatch. A route that returns no tokens despite requests succeeding at the API level is usually a provider-side issue, not an orchestrator bug.