How to use
- Copy the installation command and review the source package before installing it in your own agent environment.
- Check the source document for required tools, credentials and supported hosts.
- Describe your input and desired deliverable; review the output against the source material.
npx skills add https://github.com/daymade/claude-code-skills --skill doc-to-markdownBefore you start
- Installation does not include a model subscription, API allowance or permission to access your files.
- Repository stars and installation counts describe activity, not an independent quality or security test.
Rendered from the source repository. Headings, examples, code, tables, links, and referenced images are preserved.
Doc to Markdown
Convert documents to high-quality markdown with intelligent multi-tool orchestration and automatic DOCX post-processing.
Architecture: Pandoc (best-in-class extraction) + 8 post-processing fixes (our value-add).
Quick Start
# DOCX → Markdown (one command, zero manual fixes)
uv run --with pymupdf4llm --with markitdown scripts/convert.py document.docx -o output.md --assets-dir ./media
# PDF → Markdown
uv run --with pymupdf4llm --with markitdown scripts/convert.py document.pdf -o output.md
# Run tests
uv run --with pytest pytest scripts/test_convert.py -vDual Mode
| Mode | Speed | Quality | Use Case |
|---|---|---|---|
| Quick (default) | Fast | Good | Drafts, simple documents |
| Heavy | Slower | Best | Final documents, complex layouts |
Tool Selection
| Format | Quick Mode | Heavy Mode |
|---|---|---|
| pymupdf4llm | pymupdf4llm + markitdown | |
| DOCX | pandoc + post-processing | pandoc + markitdown |
| PPTX | markitdown | markitdown + pandoc |
| XLSX | markitdown | markitdown |
DOCX Post-Processing (automatic)
When converting DOCX via pandoc, 8 cleanups are applied automatically:
| Problem | Fix | Test coverage |
|---|---|---|
Grid tables (+:---+) | Single-column → blockquote, multi-column → pipe table | TestPostprocessPipeline |
Simple tables ( ---- ----) | Multi-column images → pipe table with captions | TestSimpleTable |
Image path nesting (media/media/) | Flatten to media/, absolute → relative | test_stats_tracking |
Pandoc attributes ({width="..."}) | Removed | test_pandoc_attributes_removed |
CJK bold spacing (**粗体**中文) | Add space around ** for CJK bold spans | TestCjkBoldSpacing (15 cases) |
| Indented dashed code blocks | → fenced ``` with language detection | test_code_block_with_language |
Escaped brackets (\[...\]) | → [...] | test_escaped_brackets_fixed |
Double-bracket links ([[text]](url)) | → [text](url) | test_double_bracket_links_fixed |
PDF Post-Processing (automatic, 2026-08-30 起)
When converting PDF via pymupdf4llm, 3 cleanups are applied automatically (skip with --no-postprocess):
| Problem | Fix | Test coverage |
|---|---|---|
Tesseract OCR garbage on image regions (<!-- Start of picture text -->...) | Block removed; images themselves kept | TestStripOcrPictureText |
| Repeated header/footer/watermark lines (same normalized line on ≥60% of pages, incl. diagonal watermarks) | Detected via pymupdf cross-page scan, removed from markdown; bold-wrapped and merged-with-page-number variants also caught | TestRepeatingLines |
Absolute image paths () | Rewritten relative to the output markdown file (portable output) | TestImagePathsRelative |
Heavy mode additionally prints a loud ⚠️ HEAVY MODE DEGRADED warning on stderr when one engine fails and the merge would otherwise silently degrade to single-engine output.
Known limits (learned from a 62-page Chinese research-report conversion, 2026-08-30):
- pymupdf4llm may emit duplicated paragraphs (source text layer has only one copy) — not auto-fixed; spot-check.
- Dotted TOC pages get detected as tables — rewrite the TOC manually if it matters.
- Cross-page tables are NOT merged (each page's fragment keeps its own header row) — merge manually.
- Table cells overlapped by diagonal watermarks can contain watermark character shards (
dn,uFE, ...); the repeating-line stripper removes full lines only, not intra-cell shards. Watermark-heavy PDFs need cell-level rebuild (collect non-watermark spans per cell bbox). - Complex infographics (dense in-image text) come out as images only; transcribing in-image text needs a VLM pass, not this tool.
CJK Bold Spacing — why and how
DOCX uses run-level styling (no spaces between bold/normal runs in CJK text). Markdown renderers need whitespace around ** to recognize bold boundaries.
Rule: if a **content** span contains any CJK character, ensure both sides have a space — unless already spaced or at line boundary. This handles CJK punctuation, emoji adjacency, and mixed content.
Before: 打开**飞书**,就可以 → some renderers fail to bold
After: 打开 **飞书** ,就可以 → universally renders correctlyHeavy Mode Workflow
Heavy Mode runs multiple tools in parallel and selects the best segments:
- Parallel Execution: Run all applicable tools simultaneously
- Segment Analysis: Parse each output into segments (tables, headings, images, paragraphs)
- Quality Scoring: Score each segment based on completeness and structure
- 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 ./extracted-images
# Generate markdown references file
uv run --with pymupdf scripts/extract_pdf_images.py document.pdf --markdown refs.mdOutput:
- Images:
extracted-images/img_page1_1.png,extracted-images/img_page2_1.jpg - Metadata:
extracted-images/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.htmlQuality 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 --verbosePath Conversion (Windows/WSL)
# Windows to WSL conversion
python scripts/convert_path.py "C:\Users\<windows-user>\Documents\file.pdf"
# Output: /mnt/c/Users/<windows-user>/Documents/file.pdfCommon Issues
"No conversion tools available"
# Install all tools
pip install pymupdf4llm
uv tool install "markitdown[pdf]"
brew install pandocFontBBox 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 + DOCX post-processing |
test_convert.py | 31 tests covering all post-processing functions |
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/benchmark-2026-03-22.md- 5-tool benchmark (Docling/MarkItDown/Pandoc/Mammoth/ours)references/heavy-mode-guide.md- Detailed Heavy Mode documentationreferences/tool-comparison.md- Tool capabilities comparisonreferences/conversion-examples.md- Batch operation examples
Next Step: Clean Up Converted Content
After converting documents to markdown, suggest cleanup:
Conversion complete: [N] files converted to markdown.
Options:
A) Clean up docs — run /daymade-docs:docs-cleaner to consolidate redundant content (Recommended if multiple files)
B) Check facts — run /fact-checker to verify claims in the converted content
C) No thanks — the markdown conversion is sufficient

