DeepSeek Harness 插件

dsh-mimo-agent-tools

Xiaomi MiMo search + multimodal tools for DSH agents: mimo_search/vision/audio/video/asr/tts.(英文原文)

跳到安装方式

来源信息

GitHub 仓库
ch1bug/dsh-mimo-agent-tools
最近更新
2026年8月19日
分类
自动化与任务
GitHub stars
5
载体类型
plugin
目录证据
上游声明已找到 dsh.bundle
证据路径
package.json#dsh.bundle
核对版本
0.1.0-rc.8
上游核对日期
2026-08-20

该证据由上游目录提供。本站没有安装、运行或安全审核这个插件。

安装

默认先复制一段 Prompt,让 Agent 读 GitHub 仓库和源码;需要自己装时再切到命令。

复制这段 Prompt,发给 DSH、Codex 或其他 Agent,让它先读 GitHub 仓库和源码。

请先不要安装或执行任何命令。阅读这个插件的 GitHub 仓库、README 和关键源码,然后用清楚、直接的方式回答以下问题,帮助我判断它是否适合我的需求:

1. 这个插件是什么,解决什么问题;
2. 适合哪些用户和典型使用场景;
3. 安装后如何使用,并给出一个最小使用示例;
4. 有哪些已知限制,以及隐私、安全、兼容性或维护风险;
5. 给出“推荐 / 有条件推荐 / 不推荐”的明确建议和理由。

请区分仓库明确说明、根据源码推断和未知信息。证据不足时请明确说明,不要猜测或照抄 README。

GitHub:https://github.com/ch1bug/dsh-mimo-agent-tools
插件名:dsh-mimo-agent-tools
作者:ch1bug

检查来源文件

安装前先看这个插件目录里的 README 和其他文件。

文件资源管理器3 个文件
README.md来源说明 · 只读预览

mimo-agent-tools

DSH (DeepSeek Harness) Cordis plugin that turns the Xiaomi MiMo API into model tools for an agent: web search, image/audio/video understanding, speech-to-text, and text-to-speech.

Backed by the OpenAI-compatible endpoint https://api.xiaomimimo.com/v1.

Tools

ToolModelPurpose
mimo_searchmimo-v2.5-proWeb search via the native web_search tool, returns answer + cited sources (incl. site_name/logo_url); optional force_search, user_location
mimo_thinkmimo-v2.5-pro / mimo-v2.5Deep thinking — full reasoning chain (reasoning_content) + final answer
mimo_jsonmimo-v2.5-pro / mimo-v2.5Structured JSON output via response_format: json_object
mimo_visionmimo-v2.5Image understanding — local files (auto base64) or public URLs, multi-image
mimo_audiomimo-v2.5Audio understanding / transcription (wav/mp3/flac/ogg/m4a) — local file or public URL
mimo_videomimo-v2.5Video understanding (mp4/webm/mov) — local file or public URL; optional fps / media_resolution
mimo_asrmimo-v2.5-asrSpeech-to-text with optional language hint — local file or public URL
mimo_ttsmimo-v2.5-tts / -voicedesignText-to-speech to a .wav/.mp3 file — preset voices or free-form voice design; optional style (speaking tone) and format (wav/mp3)
mimo_voiceclonemimo-v2.5-tts-voicecloneVoice cloning — reference clip + text → speech in that voice; optional format (wav/mp3)

audio-tools skill

The plugin registers an audio-tools skill that guides when to use the four audio tools (mimo_asr, mimo_tts, mimo_voiceclone, mimo_audio). The tools themselves are always registered — they are lightweight pure-API calls — so the skill only teaches usage, it does not gate the tools.

Requirements

connected-search plugin enabled in the MiMo console.

  • python3 on the host (used by driver/mimo_driver.py).
  • DSH host with the shell and sandboxPolicy services.

Configuration

The API key is resolved at tool-call time from the DSH credentials service first (key name XIAOMI_API_KEY — the web Models page writes keys there), falling back to the environment. Nothing is hardcoded:

SourceKeyPriority
DSH credentials service (~/.dsh/.credentials.yaml, web Models page)XIAOMI_API_KEY1
EnvironmentXIAOMI_API_KEY or MIMO_API_KEY2

Other options (environment, read at apply time):

Env varPurposeDefault
MIMO_DRIVERpath to driver/mimo_driver.py~/.local/lib/mimo-agent-tools/driver/mimo_driver.py
MIMO_TMPtemp dir for spec/response files/tmp

Install the driver at the default path (or point MIMO_DRIVER at it):

mkdir -p ~/.local/lib/mimo-agent-tools/driver
cp driver/mimo_driver.py ~/.local/lib/mimo-agent-tools/driver/

Why a python driver?

Multimodal payloads are multi-megabyte base64 strings. Agent shells commonly cap captured stdout (DSH's bash seam caps at 64KB), which silently truncates large payloads. The driver therefore does ALL file reading, body assembly and HTTP POSTing inside one python3 process, using spec/response files on disk — nothing large ever crosses the shell.

Install (DSH bundle)

Standard DSH bundle — install with the official plugin command (auto-inits the profile, pnpm-installs, and appends the bundle layer per dsh.bundle.patch):

# From a local checkout, or via git/npm:
dsh plugin --profile web add /path/to/dsh-mimo-agent-tools
# or: dsh plugin --profile web add github:you/dsh-mimo-agent-tools

# Install the python driver to the default path (MIMO_DRIVER points at it):
mkdir -p ~/.local/lib/mimo-agent-tools/driver
cp driver/mimo_driver.py ~/.local/lib/mimo-agent-tools/driver/

# Restart dsh web; the tools mount automatically.

Dependencies are declared as peerDependencies (ecosystem convention — @deepseek-ai/dsh-tools is already loaded in the DSH process, so nothing is duplicated). dsh plugin add installs the bundle into the profile's node_modules where peer deps resolve against the running harness.

Notes on the MiMo API (from the official docs)

  • TTS target text goes in the assistant message; the voice description

(voicedesign model) goes in the user message; a style instruction rides the user message for preset voices and becomes an inline (风格) tag prefix for voicedesign voices.

  • mimo-v2.5-tts-voicedesign does not accept an audio.voice field — it

uses optimize_text_preview instead.

  • ASR (mimo-v2.5-asr) must not receive a thinking field.
  • input_audio.data / video_url.url accept either a public URL or a

data:<mime>;base64,... data URL (video base64 capped at 50MB per the docs).

  • Web search costs per keyword round (max_keyword, default 3) — see MiMo

pricing. force_search (default true) trades freshness against cost; user_location biases results, e.g. {"type":"approximate","country":"China","region":"Hubei","city":"Wuhan"}.

  • Deep thinking (mimo_think) returns reasoning_content + content; in

multi-turn agent conversations with tool calls, reasoning_content from earlier turns must be echoed back or the API returns 400.

  • Structured output (mimo_json) needs an explicit JSON shape description in

the prompt (fields, types, nesting); keep max_completion_tokens generous so the JSON is not truncated mid-document.

Tests

python3 tests/test_driver.py   # driver request-body assembly (12 cases)
node --test tests/tools.test.mjs  # tool registration surface (9 cases)

License

MIT