多模态数据源转换引擎

SKILL研究检索
研究检索 未标注权限 许可证不明确
安装这个技能

将源文件转换为 Markdown 格式。适用于把常规文档、结构化导出文件、截图、扫描件、压缩包、音频转为 Markdown 文本。支持格式:md、txt、docx、pdf、pptx、xlsx、xls、csv、html、htm、json、xml;同时支持图片 OCR、扫描 PDF 识别、音频转写。文档与结构化文件默认使用 MarkItDown,图片调用腾讯 OCR,音频调用腾讯语音识别,异常时自动降级至 MiMo、火山引擎大模型。

一句话选型结论

按资料字段整理

多模态数据源转换引擎是研究检索类的 Agent Skill,安装方式未标注,权限级别未标注,许可证不明确,有可直接复制的安装命令。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

分类研究检索 安装方式未标注 权限级别未标注权限 许可证许可证不明确
累计安装 未标注 本周 未标注
GitHub 星标 未标注 仓库 未标注
下载量 未标注 技能市场下载数
权限级别 未标注权限 安装前请确认风险范围
许可证 许可证不明确 未说明

安装

未标注
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
skillhub install user_317b55bd/source-to-markdown
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    执行上面的命令安装;也可以把仓库里的 SKILL.md 手动放进客户端的 skills 目录。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

研究检索
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方user_317b55bd仓库 未标注 · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式未标注安装包 community
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验未标注上游最后核验时间 · 数据更新 1791734501
正文体量9.3 KBSKILL.md 原文大小,越大说明说明书写得越细

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
查资料并整理出处

让模型按主题查资料,并把引用来源整理成清单。

网页与文献要点提炼

把长文、论文、网页压成能直接看的要点。

竞品与行业汇总

按关键词汇总竞品动态与行业信息。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 有可直接复制的安装命令,不用自己翻文档找入口。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在研究检索场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
多模态数据源转换引擎当前 未标注权限 未标注 未标注 未标注 有
寻找技能 浏览器控制 GitHub 仓库 3120.0 万 Codex、Claude、Cursor 有
自我改进 Agent 接触敏感数据 ClawHub 市场 1646.4 万 OpenClaw 有
灵魂追踪 联网访问 GitHub 仓库 758.9 万 Codex、Claude、Cursor 有
自我完善 联网访问 ClawHub 市场 682.9 万 OpenClaw 有
微软代工厂 调用外部服务 GitHub 仓库 661.4 万 Codex、Claude、Cursor 有

SKILL.md 全文

9.3 KB
模型实际读到的说明书原文,来自技能仓库

Source to Markdown

Use this skill only for format conversion into Markdown. Do not perform requirement analysis, product scoping, hypothesis extraction, summaries, recommendations, handoff generation, or team coordination.

Core Contract

  • Convert source files into Markdown text.
  • Preserve original visible or spoken content as faithfully as possible.
  • Do not summarize, explain, answer, classify, or infer business meaning.
  • Do not create structured analysis files, source indexes, demo paths, hypotheses, or project deliverables.
  • Write outputs to the user-requested path; if no path is specified, use a local converted/ folder near the source or project deliverable folder.
  • Use .raw.md for OCR/ASR/LLM transcription outputs.

Supported Inputs

Input Default Handling
.md, .txt Read directly and normalize if needed
.docx Convert with MarkItDown
.pdf Convert with MarkItDown; use Tencent OCR for scanned pages
.pptx Convert slide text with MarkItDown
.xlsx, .xls Convert tables with MarkItDown
.csv Convert table export with MarkItDown
.html, .htm Convert saved web/API documentation with MarkItDown
.json Convert structured JSON dump with MarkItDown
.xml Convert structured XML/config dump with MarkItDown
.png, .jpg, .jpeg, .webp, .gif, .bmp Default Tencent OCR; visual LLM fallback
.wav, .pcm, .ogg, .speex, .silk, .mp3, .m4a, .aac, .amr Default Tencent ASR
.mp3, .wav, .m4a, .flac, .ogg LLM audio fallback when Tencent ASR is unsuitable
.zip Batch route contained files and write manifest.md

Unsupported by default: video, YouTube URLs, EPUB, and arbitrary binary dumps. Ask for a common-format export when needed.

Provider Configuration

API credentials, provider options, and local runtime paths are configured in providers.json at the skill root. Provider value precedence is:

providers.json > environment variable > script default

Read references/providers.md only when you need the full JSON template, environment fallback table, or provider fields. providers.json may contain real local secrets; never paste its values into chat, converted Markdown, logs, or user-visible output.

Route Selection

Source Default Fallback
Office/text documents MarkItDown Ask for cleaner .md, .pdf, .docx, or .csv export
CSV/HTML/JSON/XML structured exports MarkItDown Ask for cleaner .csv, .md, or source-system export
Image text OCR scripts/tencent_ocr_to_markdown.py scripts/vision_to_markdown.py
Visual layout/context transcription scripts/vision_to_markdown.py Ask for text/PDF/DOCX export
Audio transcript scripts/tencent_asr_to_markdown.py scripts/llm_audio_to_markdown.py
ZIP material package scripts/source_to_markdown.py batch router Convert files one by one and record failures

Unified Router

Prefer the unified router for normal use. It routes by file extension, writes single-file outputs, expands ZIP packages safely, and writes a batch manifest.md.

Single file:

python skills/source-to-markdown/scripts/source_to_markdown.py `
  "input.docx" `
  "converted/input.md"

Structured exports supported through MarkItDown:

python skills/source-to-markdown/scripts/source_to_markdown.py `
  "api-response.json" `
  "converted/api-response.md"

python skills/source-to-markdown/scripts/source_to_markdown.py `
  "export.csv" `
  "converted/export.md"

python skills/source-to-markdown/scripts/source_to_markdown.py `
  "saved-page.html" `
  "converted/saved-page.md"

python skills/source-to-markdown/scripts/source_to_markdown.py `
  "device-config.xml" `
  "converted/device-config.md"

Image route selection:

python skills/source-to-markdown/scripts/source_to_markdown.py `
  "input.png" `
  "converted/input.raw.md" `
  --image-route ocr

python skills/source-to-markdown/scripts/source_to_markdown.py `
  "input.png" `
  "converted/input.raw.md" `
  --image-route vision

Audio route selection:

python skills/source-to-markdown/scripts/source_to_markdown.py `
  "meeting.m4a" `
  "converted/meeting.raw.md" `
  --audio-route asr

python skills/source-to-markdown/scripts/source_to_markdown.py `
  "meeting.mp3" `
  "converted/meeting.raw.md" `
  --audio-route llm `
  --request-timeout 600

ZIP material package:

python skills/source-to-markdown/scripts/source_to_markdown.py `
  "materials.zip" `
  "converted/materials"

ZIP output layout:

converted/materials/
├── manifest.md
├── source-a.md
├── table-export.md
├── screenshot.raw.md
└── nested/path/spec.md

manifest.md records every contained file, route, output path, status, and failure/skipped reason. Do not treat failed or skipped files as converted evidence.

Document Conversion

Use MarkItDown for normal document sources:

markitdown "input.docx" -o "converted/input.md"
markitdown "input.pdf" -o "converted/input.md"
markitdown "input.pptx" -o "converted/input.md"
markitdown "input.xlsx" -o "converted/input.md"
markitdown "input.csv" -o "converted/input.md"
markitdown "input.html" -o "converted/input.md"
markitdown "input.json" -o "converted/input.md"
markitdown "input.xml" -o "converted/input.md"

For .md or .txt, read directly and preserve the original text unless normalization is explicitly requested.

For scanned PDFs, use Tencent OCR page by page when MarkItDown cannot extract text:

python skills/source-to-markdown/scripts/tencent_ocr_to_markdown.py `
  "scanned.pdf" `
  "converted/scanned-page-1.raw.md" `
  --pdf-page-number 1

On Windows, set UTF-8 output if Chinese text prints incorrectly:

$env:PYTHONIOENCODING='utf-8'

Image Conversion

Use Tencent OCR first for images, screenshots, scanned notes, and scanned PDF pages:

python skills/source-to-markdown/scripts/tencent_ocr_to_markdown.py `
  "input.png" `
  "converted/input.raw.md" `
  --request-timeout 300

For large images with small text, add:

--enable-detect-split

Use the visual LLM route only when deterministic OCR is insufficient and the image needs visual layout/context transcription:

python skills/source-to-markdown/scripts/vision_to_markdown.py `
  "input.png" `
  "converted/input.raw.md" `
  --request-timeout 300

Image output must be raw visible text or faithful visual transcription. Do not add interpretation, analysis, or conclusions.

Audio Conversion

Use Tencent ASR first for recordings:

python skills/source-to-markdown/scripts/tencent_asr_to_markdown.py `
  "meeting.m4a" `
  "converted/meeting.raw.md" `
  --request-timeout 300

Tencent ASR uses tencent_asr in providers.json, supports common recording formats, and outputs only recognized transcript text from flash_result.

Use the LLM audio route only when Tencent ASR is unavailable, unsuitable, or explicitly requested:

python skills/source-to-markdown/scripts/llm_audio_to_markdown.py `
  "meeting.mp3" `
  "converted/meeting.raw.md" `
  --request-timeout 300

For long recordings, increase timeout:

--request-timeout 600

For known-good audio on the LLM fallback route, bypass normalization only when needed:

--normalize-audio never

Audio output must be raw transcript text only. Do not add generated headings, summaries, action items, analysis, “识别不确定处”, or invented “无” sections.

Output Rules

  • Use .md for document conversions.
  • Use .md for MarkItDown-routed structured exports such as CSV, HTML, JSON, and XML.
  • Use .raw.md for OCR, ASR, and LLM transcription outputs.
  • For ZIP packages, write a manifest.md and one output file per converted source file.
  • Preserve original order, wording, numbers, timestamps, labels, and table structure as much as possible.
  • Mark unclear OCR as [无法识别] or [不确定: ...].
  • Mark unclear audio as [听不清] or [不确定: ...].
  • Do not add metadata headers unless a script option explicitly requests them.
  • Do not include API keys, provider config values, request signatures, or credentials in outputs.

Failure Handling

If conversion fails:

  1. Record the failed file and the error message.
  2. Try a simpler conversion route:
    - .docx -> ask for .pdf or .md
    - .pdf -> ask for text PDF or Word source if scanned/poorly extracted
    - .pptx -> ask for speaker notes or exported .pdf
    - .xlsx -> ask for .csv only if spreadsheet parsing fails
    - image -> clearer image, text/PDF/DOCX export, or visual LLM fallback
    - audio -> supported format, shorter audio, clearer recording, or LLM audio fallback
  3. Do not invent missing text.
  4. Report which files converted and which files failed.

常见问题

5 问
答案由本站依据条目字段整理
多模态数据源转换引擎怎么安装?

在支持 Skills 的客户端里执行:skillhub install user_317b55bd/source-to-markdown。安装方式为未标注。装完刷新技能列表或重开客户端。

多模态数据源转换引擎支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

多模态数据源转换引擎权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

多模态数据源转换引擎收费吗?

本站不代收费用,也没有标注具体价格。是否收费取决于技能本身和所用的模型或客户端,正式使用前按作者说明确认。

多模态数据源转换引擎用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

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技能内容以作者仓库为准;分类、权限级别与许可证状态的中文说明为中文整理,最近核验 未标注。