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Skillzwave

markitdown

58
F

Convert various file formats (PDF, Office documents, images, audio, web content, structured data) to Markdown optimized for LLM processing. Use when converting documents to markdown, extracting text from PDFs/Office files, transcribing audio, performing OCR on images, extracting YouTube transcripts, or processing batches of files. Supports 20+ formats including DOCX, XLSX, PPTX, PDF, HTML, EPUB, CSV, JSON, images with OCR, and audio with transcription.

Also in: markdown json word

Third-Party Agent Skill: Review the code before installing. Agent skills execute in your AI assistant's environment and can access your files. Learn more about security

Installation for Agentic Skill

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skilz install jackspace/ClaudeSkillz/markitdown
skilz install jackspace/ClaudeSkillz/markitdown --agent opencode
skilz install jackspace/ClaudeSkillz/markitdown --agent codex
skilz install jackspace/ClaudeSkillz/markitdown --agent gemini

First time? Install Skilz: pip install skilz

Works with 14 AI coding assistants

Cursor, Aider, Copilot, Windsurf, Qwen, Kimi, and more...

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Download Agent Skill ZIP

Extract and copy to ~/.claude/skills/ then restart Claude Desktop

1. Clone the repository:
git clone https://github.com/jackspace/ClaudeSkillz
2. Copy the agent skill directory:
cp -r ClaudeSkillz/skills/scientific-pkg-markitdown ~/.claude/skills/
View on GitHub

Need detailed installation help? Check our platform-specific guides:

Claude Desktop Guide Claude Code Guide Troubleshooting

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Agentic Skill Details

Owner
jackspace (GitHub)
Repository
ClaudeSkillz
Type
Technical
Meta-Domain
productivity
Primary Domain
pdf
Market Score
58
Agentic Skill Grades →

Agent Skill Grade

F
Score: 58/100 Click to see breakdown

Score Breakdown

Spec Compliance
11/15
PDA Architecture
14/30
Ease of Use
19/25
Writing Style
7/10
Utility
11/20
Modifiers: -4

Areas to Improve

  • Missing Reference Files
  • Missing Batch Script
  • No Table of Contents

Recommendations

  • Focus on improving Pda (currently 14/30)
  • Focus on improving Utility (currently 11/20)
  • Address 2 high-severity issues first

Graded: 2026-01-05

Developer Feedback

I took a look at your scientific-pkg-markitdown skill and wanted to share some thoughts.

Links:

The TL;DR

You're at 58/100, which lands in F territory. This is based on Anthropic's best practices for skill design. Your strongest area is Ease of Use (19/25) – the metadata and trigger terms are solid – but Progressive Disclosure Architecture (14/30) and Utility (11/20) are dragging things down. The good news? There are some concrete, high-impact fixes that'll move the needle significantly.

What's Working Well

  • Trigger terms are strong: Your "When to Use" section nails real use cases (document conversion, OCR extraction, transcription) that'll help people find this skill at the right moment
  • Format coverage is comprehensive: The list of supported formats (PDF, DOCX, PPTX, audio, video) shows you've thought about what MarkItDown actually does
  • Clear naming and description: "Convert documents to Markdown" is straightforward, and your frontmatter YAML is valid with all required fields

The Big One: Ghost Reference Files

Here's the problem: your skill references 6 files in a references/ directory that don't actually exist (document_conversion.md, media_processing.md, etc.). Same issue with scripts/batch_convert.py. This breaks the entire layered architecture and tanks your PDA score.

The fix: Either create these files with actual content (which would push you +8 points easily), or remove the references entirely. If you go the creation route, these would be solid additions:

  • references/document_conversion.md – API usage patterns, format matrix
  • references/batch_processing.md – Example script for bulk conversions
  • references/troubleshooting.md – C...

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