pdf-to-html

$npx mdskill add daymade/claude-code-skills/pdf-to-html

Converts PDFs to readable HTML with images, tables, and optional translation

  • Solves the problem of reading PDFs on web or mobile with layout intact
  • Uses PyMuPDF for extraction, headless Chrome for verification, and base64 image inlining
  • Preserves font size, layout, and reading order while detecting translation needs
  • Delivers a single, styled HTML file that is visually verified for accuracy

SKILL.md

.github/skills/pdf-to-htmlView on GitHub ↗
---
name: pdf-to-html
description: Converts a PDF into one self-contained, readable HTML file that preserves images, tables, charts and reading order — optionally translating it into another language while keeping every figure. Uses structured extraction (PyMuPDF), font-size-driven layout, compressed base64-inlined images (a single portable file), and mandatory headless-Chrome visual verification. Use whenever someone wants to READ a PDF as a web page or clean document, turn a PDF into HTML, or translate a PDF into another language while keeping its images/tables/charts intact — e.g. "PDF 转 HTML", "把这个 PDF 转成中文网页版", "make this report readable", "translate this PDF but don't lose the charts", "I just want to read this PDF on my phone". Distinct from doc-to-markdown (plain Markdown text) and pdf-creator (Markdown→PDF) — this one produces a styled, image-faithful HTML reading experience.
---

# PDF to HTML

Turn a PDF into a single, self-contained, readable HTML file — images, tables,
charts and reading order preserved — and optionally translate it, keeping every
figure in place.

The pipeline is **extract → look → (translate) → build → verify**. The middle
"look" and final "verify" steps are where faithfulness actually comes from: a PDF
is a layout, not just a text stream, so you read the rendered pages before
building and the rendered HTML before delivering.

This skill runs **inline** (no `context: fork`): translation orchestrates a
Dynamic Workflow, and a subagent cannot spawn one.

## When to use / not use

- **Use** when the goal is to *read* a PDF as HTML/web page, to convert a PDF to
  a styled HTML document, or to translate a PDF into another language while
  keeping its figures and tables.
- **doc-to-markdown** instead if they want plain Markdown text (no styling, figures optional).
- **pdf-creator** instead for the reverse direction (Markdown → PDF).

## What it does NOT do

- **Scanned/image-only PDFs** (no text layer): OCR first (e.g. `ocrmypdf`), then use this.
- **Complex multi-column tables**: cell *text* is preserved and readable, but column
  alignment can flatten into a text flow — PyMuPDF reads a table as text blocks, not a
  grid, so the grid lines are gone. Tables that are *images* in the PDF survive as
  images. If the table's grid structure is essential, use **doc-to-markdown** (pandoc
  rebuilds real tables) or convert that page separately.
- **Pixel-perfect facsimile**: output is a clean *re-flow* that keeps images and
  reading order, not a 1:1 copy of the original page layout.
- **Rewriting**: it translates and re-lays-out; it does not summarize, add a TL;DR,
  or editorialize. Faithfulness is the point (see Fidelity below).

## Dependencies

`uv` (runs Python with inline deps), Google Chrome or Chromium (visual
verification). Python packages come via `uv run --with`: PyMuPDF, Pillow, numpy.
Nothing to pre-install beyond Chrome and uv.

## Workflow

Copy this checklist and tick as you go:

```
- [ ] 1. Extract structure + render pages   (extract_pdf.py)
- [ ] 2. Read pages/*.png — SEE the layout, find content vs decorative images
- [ ] 3. (only if translating) run the translation workflow
- [ ] 4. Build the single-file HTML          (build_html.py)
- [ ] 5. Verify visually                      (verify_render.py → Read every segment)
- [ ] 6. Deliver the .html
```

### 1. Extract

```bash
uv run --with pymupdf python scripts/extract_pdf.py input.pdf
```

Writes `input-build/` with `structure.json` (text blocks with font sizes + image
blocks flagged `decorative`), `images/`, and `pages/` (one PNG per page).

### 2. Look before you build

Read `input-build/pages/*.png`. This is not optional: you need to see the real
layout, confirm which images are content vs decoration, and spot tables/charts.
For a long PDF, read every page; for a short one it's quick. This is also where
you understand the document well enough to translate it well.

### 3. Translate (optional)

Only if the user asked for another language. Read
[references/translation_workflow.md](references/translation_workflow.md) and
follow it: a Dynamic Workflow translates pages in parallel, captions data charts,
and reconciles terminology. It produces two overlay files (`units.json`,
`caps.json`) that step 4 consumes. **Do not** hand-translate inline for anything
longer than a page — the workflow keeps terminology consistent and is far faster.

### 4. Build

```bash
# original-language HTML
uv run --with Pillow python scripts/build_html.py input-build/structure.json --out output.html

# translated HTML (overlays from step 3)
uv run --with Pillow python scripts/build_html.py input-build/structure.json --out output.html \
    --translation input-build/units.json --captions input-build/caps.json --lang zh-CN
```

`build_html.py` is **data-driven**: it infers heading levels from font size (most
common size = body; larger steps up to h3/h2/h1), drops decorative images, and
inlines content images as compressed base64 → one portable file. It is not
hand-tuned to any document. If a particular PDF has an unusual structure (e.g.
multi-column, sidebars, a figure the size heuristic misreads), read the script and
adjust — it's short and meant to be edited per document.

### 5. Verify visually (mandatory)

```bash
uv run --with Pillow --with numpy python scripts/verify_render.py output.html
```

Then **Read every `seg-*.png`** and check: fonts render (no tofu boxes), no
clipped tables/figures, headings/lists look right, all expected images present.
Text being correct does not mean the render is correct (failure_cases #7). Fix and
re-verify until it's clean.

A quick structural cross-check is fine too, but count occurrences correctly:
`grep -o '<figure>' output.html | wc -l` — **not** `grep -c` (failure_cases #1).

### 6. Deliver

Hand over the single `.html`. It's self-contained (images inlined), so it opens
with a double-click and nothing can go missing.

## Scripts

| Script | Run with | Purpose |
|--------|----------|---------|
| `scripts/extract_pdf.py` | `uv run --with pymupdf` | PDF → structure.json + images/ + page renders |
| `scripts/build_html.py` | `uv run --with Pillow` | structure.json (+ optional translation/captions) → single-file HTML |
| `scripts/verify_render.py` | `uv run --with Pillow --with numpy` | headless-Chrome render → readable PNG segments |

## Fidelity (read before translating)

The deliverable looks authoritative, so wrong content is worse than ugly content.
The non-negotiable rules — and the specific ways this has gone wrong before — are
in [references/failure_cases.md](references/failure_cases.md). The one that bites
hardest: **never give a real person an inferred translated name, and copy every
number/proper-noun verbatim** (failure_cases #6). Read that file before any
translation run; skim it before any run.

## Next Step

After producing the HTML, suggest the natural follow-up:

```
Conversion complete: output.html (single self-contained file).

Options:
A) Make a PDF of it — run /daymade-docs:pdf-creator if you want a print/share copy (Recommended if they need to send it)
B) Extract the text as Markdown instead — run /daymade-docs:doc-to-markdown (if they wanted editable text, not a reading page)
C) No thanks — the HTML is what I wanted
```

More from daymade/claude-code-skills

SkillDescription
asr-transcribe-to-textTranscribes audio and video files to text using Qwen3-ASR. Supports two modes — local MLX inference on macOS Apple Silicon (no API key, 15-27x realtime) and remote API via vLLM/OpenAI-compatible endpoints. Auto-detects platform and recommends the best path. Triggers when the user wants to transcribe recordings, convert audio/video to text, do speech-to-text, or mentions ASR, Qwen ASR, 转录, 语音转文字, 录音转文字. Also triggers for meeting recordings, lectures, interviews, podcasts, screen recordings, or any audio/video file the user wants converted to text.
auto-repo-setup|
benchmark-due-diligence>
bigdata-skill>-
capture-screenProgrammatic screenshot capture on macOS. Find window IDs with Swift CGWindowListCopyWindowInfo, control application windows via AppleScript (zoom, scroll, select), and capture with screencapture. Use when automating screenshots, capturing application windows for documentation, or building multi-shot visual workflows.
claude-code-history-files-finderFinds and recovers content from Claude Code session history files. This skill should be used when searching for deleted files, tracking changes across sessions, analyzing conversation history, or recovering code from previous Claude interactions. Triggers include mentions of "session history", "recover deleted", "find in history", "previous conversation", or ".claude/projects".
claude-md-progressive-disclosurer|
claude-skills-troubleshootingDiagnose and resolve Claude Code plugin and skill issues. This skill should be used when plugins are installed but not showing in available skills list, skills are not activating as expected, or when troubleshooting enabledPlugins configuration in settings.json. Triggers include "plugin not working", "skill not showing", "installed but disabled", or "enabledPlugins" issues.
cli-demo-generatorGenerates professional animated CLI demos as GIFs using VHS terminal recordings. Handles tape file creation, self-bootstrapping demos with hidden setup, output noise filtering, post-processing speed-up, and frame-level verification. Use when users want to create terminal demos, record CLI workflows as GIFs, generate animated documentation, build demo tapes for README files, or need to showcase any command-line tool visually. Also triggers on "record terminal", "VHS tape", "demo GIF", "animate my CLI", or any request to visually demonstrate shell commands.
cloudflare-troubleshootingInvestigate and resolve Cloudflare configuration issues using API-driven evidence gathering. Use when troubleshooting ERR_TOO_MANY_REDIRECTS, SSL errors, DNS issues, or any Cloudflare-related problems. Focus on systematic investigation using Cloudflare API to examine actual configuration rather than making assumptions.