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
bash# 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 -v
Dual 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 correctly
Heavy 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
bash# 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.md
Output:
- Images:
extracted-images/img_page1_1.png,extracted-images/img_page2_1.jpg - Metadata:
extracted-images/images_metadata.json(page, position, dimensions)
Quality Validation
bash# 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
bash# 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)
bash# Windows to WSL conversion python scripts/convert_path.py "C:\Users\<windows-user>\Documents\file.pdf" # Output: /mnt/c/Users/<windows-user>/Documents/file.pdf
Common Issues
"No conversion tools available"
bash# 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 + 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

