paper2html — Paper to single-page project homepage (you-led, coordinated)

paper2html — Paper to single-page project homepage (you-led, coordinated)

Turn a paper PDF into a self-contained, publish-ready single-page project website — the kind of paper homepage researchers commonly build on GitHub Pages. You are the lead author: this file is the recipe, not a fully automated script — there is no main.py, no renderer. The mechanical steps (parse / extract / QA) call the small tools under scripts/; understanding the paper, designing the page, and writing index.html are done by you (read the material and figures with Read, write index.html with Write), confirming with the user at key points via AskUserQuestion.

PDF
 → parse + extract        (parse_pdf.py: MinerU → clean.md + manifest.json + images/, gate 1)
 → you understand it + set the design   (read manifest + clean.md + look at figures) → pick a design language   [confirm design direction]
 → you hand-author the page   (per the references/ design-language and authoring rules) → index.html            [optional confirm]
 → QA validation          (validate.py: missing figures/broken links/content fidelity, gate 2) → fix per report, loop
 → single-page project homepage index.html (+ images/, deployable as-is)

How you run this skill

1. Step by step: run scripts for the mechanical steps via Bash (absolute paths, no cd needed); do the design and authoring yourself with Read/Write.
2. Compute WORKDIR inline at the top of each Bash block (each Bash call is a separate shell and does not share variables):

   WORKDIR="$(dirname "$pdf_path")/.paper2anything/html/$(basename "${pdf_path%.*}")"
   

   $pdf_path is the paper PDF the user gave (reset it in each block). The scripts live in ${SKILL_DIR}/scripts — SKILL_DIR is this skill's directory (see "Base directory for this skill: …" injected at the top of this skill); each Bash block is a separate shell, so in the blocks that use it export SKILL_DIR=<that directory> once at the top (set it inline each time, like WORKDIR).
3. Pause at decision points with AskUserQuestion: after understanding the paper, confirm the design direction (design language / primary color / emphasis); after the draft is done, you may confirm again.
4. Faithful to the manifest, you fill the gaps: use only the real material in manifest.json, don't fabricate numbers/authors/links; fields the manifest left empty (authors/abstract/links etc.) you complete from the full text of clean.md — you are the lead author, deterministic extraction is only scaffolding.

Step 0: Environment and credentials

Unified environment: all python commands run in paper2anything's unified conda environment (top-level environment.yml), prefixed with conda run -n paper2anything --no-capture-output.

Credentials are centralized in the package-root .env (copied from .env.example, already gitignored); export it once per new shell: