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mimo-omni
使用小米 MiMo 的多模态模型分析和理解图片、视频和音频。当用户发送图片/视频/音频附件,询问视觉内容,请求图片描述、OCR、物体检测、场景理解、视频分析或音频转录/理解时使用。
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
메뉴
使用小米 MiMo 的多模态模型分析和理解图片、视频和音频。当用户发送图片/视频/音频附件,询问视觉内容,请求图片描述、OCR、物体检测、场景理解、视频分析或音频转录/理解时使用。
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Learns how the user writes from their own sent messages and docs, and builds a voice profile so future drafts sound like them instead of generic AI. The profile is saved as the my-writing-style skill. Use when the user asks to set up, learn, or capture their writing voice, or complains that drafts sound generic or unlike them and no my-writing-style profile exists. Only for drafting text the user will send as themselves, not for Claude's own replies.
Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files) or Word templates (.dotx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', '.dotx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx or .dotx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.
Use this skill any time a .pptx or .potx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx or .potx file (even if the extracted content will be used elsewhere, like in an email or summary); editing, modifying, or updating existing presentations; combining or splitting slide files; working with templates (.potx), layouts, speaker notes, or comments. Trigger whenever the user mentions "deck," "slides," "presentation," or references a .pptx or .potx filename, regardless of what they plan to do with the content afterward. If a .pptx or .potx file needs to be opened, created, or touched, use this skill.
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .xltx, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
Use this skill when replying with a generated or edited image — when a post asks to create, generate, edit, modify, restyle, combine, or stitch images, or whenever attaching a generated or edited image would strengthen the reply.
统一处理网页应用的生成、编辑,以及围绕已生成产物的问答。既负责把自然语言需求端到端转成可运行、可预览、可交付的网页应用产物,也负责在用户追问产物时基于真实产物作答。当用户要生成网站、H5、网页应用、管理后台、数据看板时使用。当用户要编辑已有网页应用、做功能新增、页面调整或 Bug 修复时使用。当用户提供 PRD、文档、截图或素材包并要求产出可预览网页应用时使用。当用户针对已生成的网页应用,要求总结或解读网页内容、查看或分析源码、解释或排查运行报错、查询访问量/用户量/数据报表/发布状态等运营信息时同样使用。
| name | mimo-omni |
| description | 使用小米 MiMo 的多模态模型分析和理解图片、视频和音频。当用户发送图片/视频/音频附件,询问视觉内容,请求图片描述、OCR、物体检测、场景理解、视频分析或音频转录/理解时使用。 |
通过 mimo_api.sh(Curl)或 mimo_api.py(Python)调用小米 MiMo 多模态模型,支持图片、视频、音频输入。两个工具参数完全一致。
优先使用
bash mimo_api.sh,仅当 bash/curl 不可用时才回退到python mimo_api.py。
问题参数支持任意自然语言,直接传入用户的原始 query 即可:
# 用户问什么就传什么,不需要改写
bash mimo_api.sh image /path/to/photo.jpg "<用户的问题>"
bash mimo_api.sh video /path/to/video.mp4 "<用户的问题>" --fps 1
bash mimo_api.sh audio /path/to/audio.wav "<用户的问题>"
# 示例:用户问「这张图里的猫是什么品种?」
bash mimo_api.sh image /path/to/cat.jpg "这张图里的猫是什么品种?"
# 示例:用户问「视频里的人在做什么运动?从几分几秒开始的?」
bash mimo_api.sh video /path/to/clip.mp4 "视频里的人在做什么运动?从几分几秒开始的?" --fps 2
# 示例:用户问「帮我把这段录音翻译成英文」
bash mimo_api.sh audio /path/to/recording.mp3 "帮我把这段录音翻译成英文"
# 单图(URL)
bash mimo_api.sh image "https://example.com/photo.jpg" "描述这张图片" --max-tokens 65536
python mimo_api.py image "https://example.com/photo.jpg" "描述这张图片" --max-tokens 65536 # fallback
# 单图(本地文件)
bash mimo_api.sh image /path/to/image.png "图中有哪些物体?" --max-tokens 65536
python mimo_api.py image /path/to/image.png "图中有哪些物体?" --max-tokens 65536 # fallback
# 图片 OCR
bash mimo_api.sh image /path/to/screenshot.png "提取图中所有文字,保持排版结构" --max-tokens 262144
python mimo_api.py image /path/to/screenshot.png "提取图中所有文字,保持排版结构" --max-tokens 262144 # fallback
# 图表分析
bash mimo_api.sh image /path/to/chart.png "分析图表的趋势和关键数据点" --max-tokens 262144
python mimo_api.py image /path/to/chart.png "分析图表的趋势和关键数据点" --max-tokens 262144 # fallback
# 多图对比
bash mimo_api.sh images /path/to/img1.jpg /path/to/img2.jpg --question "比较这两张图片的异同" --max-tokens 65536
python mimo_api.py images /path/to/img1.jpg /path/to/img2.jpg --question "比较这两张图片的异同" --max-tokens 65536 # fallback
参数说明:--fps 每秒采样帧数,--resolution 分辨率模式(default/max)
# 通用视频描述
bash mimo_api.sh video /path/to/video.mp4 "描述视频内容" --fps 1 --max-tokens 65536
python mimo_api.py video /path/to/video.mp4 "描述视频内容" --fps 1 --max-tokens 65536 # fallback
# 短视频(<30s,信息密度高)
bash mimo_api.sh video /path/to/short.mp4 "详细描述视频内容" --fps 2 --max-tokens 65536
python mimo_api.py video /path/to/short.mp4 "详细描述视频内容" --fps 2 --max-tokens 65536 # fallback
# 长视频摘要(>5min,控制 token)
bash mimo_api.sh video /path/to/long.mp4 "用3-5句话概括核心内容" --fps 0.5 --max-tokens 262144
python mimo_api.py video /path/to/long.mp4 "用3-5句话概括核心内容" --fps 0.5 --max-tokens 262144 # fallback
# 动作识别 / 体育赛事(高帧率)
bash mimo_api.sh video /path/to/sports.mp4 "识别视频中的关键动作" --fps 4 --max-tokens 65536
python mimo_api.py video /path/to/sports.mp4 "识别视频中的关键动作" --fps 4 --max-tokens 65536 # fallback
# 视频 OCR / 字幕提取(高分辨率)
bash mimo_api.sh video /path/to/video.mp4 "识别视频中所有文字" --fps 2 --resolution max --max-tokens 262144
python mimo_api.py video /path/to/video.mp4 "识别视频中所有文字" --fps 2 --resolution max --max-tokens 262144 # fallback
# 教学视频 / PPT 录屏(画面慢但文字多)
bash mimo_api.sh video /path/to/tutorial.mp4 "提取视频中的知识点" --fps 0.5 --resolution max --max-tokens 262144
python mimo_api.py video /path/to/tutorial.mp4 "提取视频中的知识点" --fps 0.5 --resolution max --max-tokens 262144 # fallback
# 视频中的图表分析
bash mimo_api.sh video /path/to/data.mp4 "分析视频中的图表数据" --fps 1 --resolution max --max-tokens 262144
python mimo_api.py video /path/to/data.mp4 "分析视频中的图表数据" --fps 1 --resolution max --max-tokens 262144 # fallback
# 多语言字幕翻译
bash mimo_api.sh video /path/to/foreign.mp4 "翻译视频中的字幕为中文" --fps 2 --resolution max --max-tokens 262144
python mimo_api.py video /path/to/foreign.mp4 "翻译视频中的字幕为中文" --fps 2 --resolution max --max-tokens 262144 # fallback
| 场景 | --fps | --resolution | --max-tokens |
|---|---|---|---|
| 通用描述 | 1 | default | 65536 |
| 短视频 (<30s) | 2 | default | 65536 |
| 长视频摘要 (>5min) | 0.5 | default | 262144 |
| 动作识别 / 体育 | 4~8 | default | 65536 |
| OCR / 字幕提取 | 2 | max | 262144 |
| 教学 / PPT 录屏 | 0.5 | max | 262144 |
| 图表 / 数据分析 | 1 | max | 262144 |
| 字幕翻译 | 2 | max | 262144 |
Token 参考: fps=1 → ~3168 tokens,fps=4 → ~6408 tokens(同一视频)。fps 翻倍 ≈ token 翻倍。
# 音频转录(URL 直传)
bash mimo_api.sh audio "https://example.com/audio.wav" "转录音频内容" --max-tokens 65536
python mimo_api.py audio "https://example.com/audio.wav" "转录音频内容" --max-tokens 65536 # fallback
# 本地音频转录
bash mimo_api.sh audio /path/to/audio.mp3 "转录这段音频,区分说话人" --max-tokens 65536
python mimo_api.py audio /path/to/audio.mp3 "转录这段音频,区分说话人" --max-tokens 65536 # fallback
# 音频内容描述
bash mimo_api.sh audio /path/to/audio.wav "描述音频中的声音,包括语音、音乐和环境音" --max-tokens 65536
python mimo_api.py audio /path/to/audio.wav "描述音频中的声音,包括语音、音乐和环境音" --max-tokens 65536 # fallback
# 同时分析视频画面和音频内容
bash mimo_api.sh mixed --video /path/to/video.mp4 --audio /path/to/audio.mp3 "描述视频内容并转录音频" --max-tokens 262144
python mimo_api.py mixed --video /path/to/video.mp4 --audio /path/to/audio.mp3 "描述视频内容并转录音频" --max-tokens 262144 # fallback
# URL 也可以
bash mimo_api.sh mixed --video "https://example.com/v.mp4" --audio "https://example.com/a.wav" "视频讲了什么?音频说了什么?" --fps 1 --max-tokens 262144
python mimo_api.py mixed --video "https://example.com/v.mp4" --audio "https://example.com/a.wav" "视频讲了什么?音频说了什么?" --fps 1 --max-tokens 262144 # fallback
API 原始返回为 JSON:
{
"choices": [
{
"message": {
"role": "assistant",
"content": "这张图片展现了一个充满自然质感的场景。画面主体是..."
}
}
],
"usage": {
"prompt_tokens": 4026,
"completion_tokens": 474,
"total_tokens": 4500
}
}
脚本已自动解析,输出分为两部分:
[9.0s | prompt=4026, completion=474]choices[0].message.content 的纯文本处理方式:将 stdout 的内容直接作为回答返回给用户即可。
exceeded maximum size limit for video base64 data (max: 10MB)# 本地大视频会超限
bash mimo_api.sh video /path/to/large.mp4 "描述内容" # ❌ 可能超 10MB
# 改用 URL
bash mimo_api.sh video "https://example.com/large.mp4" "描述内容" # ✅
--timeout 600(10 分钟):
bash mimo_api.sh video /path/to/long.mp4 "概括内容" --fps 0.5 --timeout 600
--fps(如 1 → 0.5)--resolution default(如果之前用了 max)| 文件 | 用途 |
|---|---|
mimo_api.py | Python CLI 调用工具 |
mimo_api.sh | Bash/Curl CLI 调用工具(参数与 py 版一致) |
examples_mimo.py | Python SDK 风格的函数库 |
examples_mimo_curl.sh | Curl 调用示例集 |