File to Markdown — Skill

Overview

Convert files into clean, structured, AI-ready Markdown using the markdown.new API powered by Cloudflare Workers AI toMarkdown(). Supports 20+ formats including documents, spreadsheets, images, and structured data. No authentication required (500 requests/day per IP).

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When to Use This Skill

Use this skill whenever you need to:

• Extract text from files for LLM processing

• Convert PDFs or Office files into Markdown

• Normalize data into structured text

• Process uploaded user files

• Scrape webpage content into Markdown

• Convert images into AI-generated descriptions + content

Common AI workflows:

• RAG ingestion pipelines

• Knowledge base creation

• Document summarization

• Dataset extraction

• Spreadsheet analysis

• OCR-like extraction from images

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Supported Formats

Documents

• .pdf

• .docx

• .odt

Spreadsheets

• .xlsx

• .xls

• .xlsm

• .xlsb

• .et

• .ods

• .numbers

Images

• .jpg

• .jpeg

• .png

• .webp

• .svg

Text & Structured Data

• .txt

• .md

• .csv

• .json

• .xml

• .html

• .htm

Notes:

• Image conversion uses AI object detection + summarization.

• HTML URL conversion uses a web page pipeline.

• Uploaded HTML uses Workers AI conversion.

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API Base URL

`` https://markdown.new `

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Endpoints

1️⃣ Convert Remote File (Simple GET)

Returns plain Markdown text. ` GET /:file-url ` Example: `bash curl -s "https://markdown.new/https://example.com/report.pdf" `

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2️⃣ Convert Remote File (JSON Response)

Returns metadata + Markdown. ` GET /:file-url?format=json ` Example: `bash curl -s "https://markdown.new/https://example.com/report.pdf?format=json" `

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3️⃣ Convert Remote File via POST

Use when you want structured JSON response. ` POST / Content-Type: application/json ` Body: `json { "url": "https://example.com/report.pdf" } ` Example: `bash curl -s https://markdown.new/ \ -H "Content-Type: application/json" \ -d '{"url": "https://example.com/report.pdf"}' `

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4️⃣ Upload Local File

Use when file is not publicly accessible. ` POST /convert multipart/form-data ` Example: `bash curl -s https://markdown.new/convert \ -F "[email protected]" `

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Response Formats

URL Conversion Response

`json { "success": true, "url": "https://example.com/report.pdf", "title": "Quarterly Report", "content": "# Quarterly Report\n\n...", "method": "Workers AI (file)", "duration_ms": 1200, "tokens": 850 } `

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Upload Conversion Response

`json { "success": true, "data": { "title": "Q4 Report", "content": "# Q4 Report\n\n...", "filename": "report.xlsx", "file_type": ".xlsx", "tokens": 1250, "processing_time_ms": 320 } } `

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Best Practices for AI Agents

Prefer GET for Simple Workflows

Use: ` GET /:url ` When:

• You only need Markdown text

• Speed is important

• No metadata required

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Prefer POST for Structured Pipelines

Use POST when:

• Metadata is needed

• Token counts are required

• Monitoring or logging is implemented

• Building automation workflows

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File Upload Strategy

Use /convert only if:

• File is local

• File is private

• File requires authentication to access

Otherwise always prefer URL conversion.

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Error Handling Strategy

Agents should:

• Check "success": true

• Retry once if network failure

• Validate content length > 0

• Fallback to alternate extraction if needed

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Rate Limits

• 500 requests/day per IP without API key

• No signup required

Agents should:

• Cache results when possible

• Avoid duplicate conversions

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Integration Examples

JavaScript (Node.js)

`js const res = await fetch("https://markdown.new/", { method: "POST", headers: { "Content-Type": "application/json" }, body: JSON.stringify({ url: "https://example.com/file.pdf" }) }); const data = await res.json(); console.log(data.content); `

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Python

`python import requests res = requests.post( "https://markdown.new/", json={"url": "https://example.com/file.pdf"} ) data = res.json() print(data["content"]) ``

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Agent Decision Tree

If user provides: | Input Type | Action | | --------------- | ---------------------- | | Public file URL | Use GET or POST | | Local file | Use POST /convert | | Image | Convert then summarize | | Spreadsheet | Convert then analyze | | Webpage | Convert URL HTML |

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Output Expectations

The Markdown should be:

• Clean

• Structured

• AI-friendly

• Minimal noise

• Ready for LLM ingestion

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Limitations

• Complex PDF layouts may lose formatting

• Large spreadsheets may be truncated

• Images rely on AI interpretation accuracy

• Token limits may apply

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Summary

This skill provides a universal file-to-Markdown conversion layer for AI systems with:

• No authentication

• Simple HTTP interface

• Multi-format support

• Structured output

• Fast processing

Ideal for document ingestion, RAG pipelines, and automation agents.

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