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daymade/claude-code-skills · updated Apr 8, 2026

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$npx skills add https://github.com/daymade/claude-code-skills --skill markdown-tools
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summary

Convert documents to high-quality markdown with intelligent multi-tool orchestration.

skill.md

Markdown Tools

Convert documents to high-quality markdown with intelligent multi-tool orchestration.

Dual Mode Architecture

Mode Speed Quality Use Case
Quick (default) Fast Good Drafts, simple documents
Heavy Slower Best Final documents, complex layouts

Quick Start

Installation

# Required: PDF/DOCX/PPTX support
uv tool install "markitdown[pdf]"
pip install pymupdf4llm
brew install pandoc

Basic Conversion

# Quick Mode (default) - fast, single best tool
uv run --with pymupdf4llm --with markitdown scripts/convert.py document.pdf -o output.md

# Heavy Mode - multi-tool parallel execution with merge
uv run --with pymupdf4llm --with markitdown scripts/convert.py document.pdf -o output.md --heavy

# Check available tools
uv run scripts/convert.py --list-tools

Tool Selection Matrix

Format Quick Mode Tool Heavy Mode Tools
PDF pymupdf4llm pymupdf4llm + markitdown
DOCX pandoc pandoc + markitdown
PPTX markitdown markitdown + pandoc
XLSX markitdown markitdown

Tool Characteristics

  • pymupdf4llm: LLM-optimized PDF conversion with native table detection and image extraction
  • markitdown: Microsoft's universal converter, good for Office formats
  • pandoc: Excellent structure preservation for DOCX/PPTX

Heavy Mode Workflow

Heavy Mode runs multiple tools in parallel and selects the best segments:

  1. Parallel Execution: Run all applicable tools simultaneously
  2. Segment Analysis: Parse each output into segments (tables, headings, images, paragraphs)
  3. Quality Scoring: Score each segment based on completeness and structure
  4. Intelligent Merge: Select best version of each segment across tools

Merge Criteria

Segment Type Selection Criteria
Tables More rows/columns, proper header separator
Images Alt text present, local paths preferred
Headings Proper hierarchy, appropriate length
Lists More items, nested structure preserved
Paragraphs Content completeness

Image Extraction

# Extract images with metadata
uv run --with pymupdf scripts/extract_pdf_images.py document.pdf -o ./assets

# Generate markdown references file
uv run --with pymupdf scripts/extract_pdf_images.py document.pdf --markdown refs.md

Output:

  • Images: assets/img_page1_1.png, assets/img_page2_1.jpg
  • Metadata: assets/images_metadata.json (page, position, dimensions)

Quality Validation

# Validate conversion quality
uv run --with pymupdf scripts/validate_output.py document.pdf output.md

# Generate HTML report
uv run --with pymupdf scripts/validate_output.py document.pdf output.md --report report.html

Quality Metrics

Metric Pass Warn Fail
Text Retention >95% 85-95% <85%
Table Retention 100% 90-99% <90%
Image Retention 100% 80-99% <80%

Merge Outputs Manually

# Merge multiple markdown files
python scripts/merge_outputs.py output1.md output2.md -o merged.md

# Show segment attribution
python scripts/merge_outputs.py output1.md output2.md -o merged.md --verbose

Path Conversion (Windows/WSL)

# Windows → WSL conversion
python scripts/convert_path.py "C:\Users\name\Documents\file.pdf"
# Output: /mnt/c/Users/name/Documents/file.pdf

Common Issues

"No conversion tools available"

# Install all tools
pip install pymupdf4llm
uv tool install "markitdown[pdf]"
brew install pandoc

FontBBox warnings during PDF conversion

  • Harmless font parsing warnings, output is still correct

Images missing from output

  • Use Heavy Mode for better image preservation
  • Or extract separately with scripts/extract_pdf_images.py

Tables broken in output

  • Use Heavy Mode - it selects the most complete table version
  • Or validate with scripts/validate_output.py

Bundled Scripts

Script Purpose
convert.py Main orchestrator with Quick/Heavy mode
merge_outputs.py Merge multiple markdown outputs
validate_output.py Quality validation with HTML report
extract_pdf_images.py PDF image extraction with metadata
convert_path.py Windows to WSL path converter

References

  • references/heavy-mode-guide.md - Detailed Heavy Mode documentation
  • references/tool-comparison.md - Tool capabilities comparison
  • references/conversion-examples.md - Batch operation examples
how to use markdown-tools

How to use markdown-tools on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • ›Cursor installed and configured on your development machine
  • ›Node.js version 16.0+ with npm package manager (verify with node --version)
  • ›Active project directory or workspace where you want to add markdown-tools
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/daymade/claude-code-skills --skill markdown-tools

The skills CLI fetches markdown-tools from GitHub repository daymade/claude-code-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/markdown-tools

Reload or restart Cursor to activate markdown-tools. Access the skill through slash commands (e.g., /markdown-tools) or your agent's skill management interface.

⚠

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

Additional Resources

›View source code on GitHub›Skills CLI documentation›Learn more about Cursor›What are agent skills?

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases▌

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

✓

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

✓

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

✓

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

✓

Save 3-5 hours/week on communication overhead

Implementation Guide▌

Prerequisites

  • ›Claude Desktop or compatible AI client
  • ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • ›Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • ⚠Not validating competitive research—verify facts before sharing
  • ⚠Accepting user stories without involving engineering team
  • ⚠Over-relying on frameworks without qualitative judgment
  • ⚠Not customizing outputs to company culture and communication style
  • ⚠Skipping stakeholder validation of generated requirements

Best Practices▌

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • −Don't publish competitive analysis without fact-checking
  • −Don't finalize user stories without engineering review
  • −Don't make prioritization decisions solely on AI scoring
  • −Don't skip customer validation of generated requirements
  • −Don't ignore company-specific context and culture

💡 Pro Tips

  • ★Provide context: company goals, constraints, customer feedback
  • ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • ★Use skill for 70% generation + 30% customization to company needs

When to Use This▌

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path▌

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.5★★★★★65 reviews
  • ★★★★★Sakura Choi· Dec 28, 2024

    Keeps context tight: markdown-tools is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • ★★★★★Ren Johnson· Dec 16, 2024

    We added markdown-tools from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • ★★★★★Emma Mehta· Dec 8, 2024

    markdown-tools fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • ★★★★★Ganesh Mohane· Dec 4, 2024

    Useful defaults in markdown-tools — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • ★★★★★Neel Tandon· Nov 27, 2024

    Registry listing for markdown-tools matched our evaluation — installs cleanly and behaves as described in the markdown.

  • ★★★★★Sakshi Patil· Nov 23, 2024

    markdown-tools is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • ★★★★★Ren Kapoor· Nov 19, 2024

    I recommend markdown-tools for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • ★★★★★Soo Lopez· Nov 7, 2024

    markdown-tools reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • ★★★★★Liam Sethi· Oct 26, 2024

    Registry listing for markdown-tools matched our evaluation — installs cleanly and behaves as described in the markdown.

  • ★★★★★Chinedu Khanna· Oct 18, 2024

    markdown-tools reduced setup friction for our internal harness; good balance of opinion and flexibility.

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