install
source · Clone the upstream repo
git clone https://github.com/openclaw/skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/alaminrifat/file-to-markdown" ~/.claude/skills/clawdbot-skills-file-to-markdown && rm -rf "$T"
manifest:
skills/alaminrifat/file-to-markdown/SKILL.mdsource content
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).
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
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.
API Base URL
https://markdown.new
Endpoints
1️⃣ Convert Remote File (Simple GET)
Returns plain Markdown text.
GET /:file-url
Example:
curl -s "https://markdown.new/https://example.com/report.pdf"
2️⃣ Convert Remote File (JSON Response)
Returns metadata + Markdown.
GET /:file-url?format=json
Example:
curl -s "https://markdown.new/https://example.com/report.pdf?format=json"
3️⃣ Convert Remote File via POST
Use when you want structured JSON response.
POST / Content-Type: application/json
Body:
{ "url": "https://example.com/report.pdf" }
Example:
curl -s https://markdown.new/ \ -H "Content-Type: application/json" \ -d '{"url": "https://example.com/report.pdf"}'
4️⃣ Upload Local File
Use when file is not publicly accessible.
POST /convert multipart/form-data
Example:
curl -s https://markdown.new/convert \ -F "file=@document.pdf"
Response Formats
URL Conversion Response
{ "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 }
Upload Conversion Response
{ "success": true, "data": { "title": "Q4 Report", "content": "# Q4 Report\n\n...", "filename": "report.xlsx", "file_type": ".xlsx", "tokens": 1250, "processing_time_ms": 320 } }
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
Prefer POST for Structured Pipelines
Use POST when:
- Metadata is needed
- Token counts are required
- Monitoring or logging is implemented
- Building automation workflows
File Upload Strategy
Use
/convert only if:
- File is local
- File is private
- File requires authentication to access
Otherwise always prefer URL conversion.
Error Handling Strategy
Agents should:
- Check
"success": true - Retry once if network failure
- Validate content length > 0
- Fallback to alternate extraction if needed
Rate Limits
- 500 requests/day per IP without API key
- No signup required
Agents should:
- Cache results when possible
- Avoid duplicate conversions
Integration Examples
JavaScript (Node.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);
Python
import requests res = requests.post( "https://markdown.new/", json={"url": "https://example.com/file.pdf"} ) data = res.json() print(data["content"])
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 |
Output Expectations
The Markdown should be:
- Clean
- Structured
- AI-friendly
- Minimal noise
- Ready for LLM ingestion
Limitations
- Complex PDF layouts may lose formatting
- Large spreadsheets may be truncated
- Images rely on AI interpretation accuracy
- Token limits may apply
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.