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Get Started Free →Render academic Markdown documents (English or Korean) to publication-quality PDF via pandoc + xelatex. Targets non-bibliography artifacts: research proposals, IRB cover letters, briefing handouts, anchor docs (Q&A grids), and reference tables. Auto-infers pipe-table column widths from content (label column shrinks to fit, data columns share remaining width). CJK-aware font fallback for Korean text (Apple SD Gothic Neo on macOS, Noto Sans CJK KR on Linux). NOT for: manuscripts with bibliography
.claude/skills/aperivue-render-pdf-doc/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | -33% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 15% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 5% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 119% | 0% |
| case-19 | ✗→✓ | ▲ Improved | -19% | 0% |
Markdown + frontmatter → publication-quality academic PDF (English or Korean).
In real circulation cycles for academic PDFs, two recurring failure patterns appear:
Manual fixes work but the same pattern recurs across proposals, briefings, IRB covers, exemption applications. This skill focuses on layout (CJK fonts + table column widths). Bibliography and CSL are handled by /manage-refs.
| Task | Skill | |---|---| | Manuscript + bibliography → DOCX/PDF | /manage-refs scripts/render_pandoc.sh (CSL + .bib) | | Filling an institutional .docx form | /fill-protocol | | ICMJE COI form | /fill-icmje-coi | | Figure / PPTX | /make-figures, /present-paper | | This skill: non-bib academic markdown → PDF (proposal, briefing, anchor doc, IRB cover) | /render-pdf-doc |
mainfont + CJKmainfont. The default fallback is OS-detected.redact_internal: true option.tbl-colwidths has reported PDF regressions (issues 6089/9200).bash# macOS brew install pandoc brew install --cask mactex-no-gui # xelatex + xeCJK (~5 GB) # Linux sudo apt-get install pandoc texlive-xetex texlive-lang-cjk fonts-noto-cjk # Windows (PowerShell) — run in Git Bash afterwards winget install --id JohnMacFarlane.Pandoc winget install --id MiKTeX.MiKTeX # xelatex; installs missing LaTeX packages on demand # No CJK font download needed: Malgun Gothic ships with Windows 7+ and is the default here.
Detection:
bashbash scripts/check_deps.sh
Windows / Git Bash note. MiKTeX's binary directory (%LOCALAPPDATA%\Programs\MiKTeX\miktex\bin\x64) is often not on the Git Bash PATH, so xelatex can read as [MISS] even after install. Both check_deps.sh and render_pdf.sh now auto-probe that location; if xelatex still isn't found, add the directory to your PATH (or run from the MiKTeX Console → Settings-configured shell). The Windows CJK/main font default is Malgun Gothic (preinstalled); override per document via frontmatter, or with --font / --cjk-font.
yaml--- title: "Paper 2 Calibration Anchor — Q&A Grid" author: "<Author Group>" date: "2026-05-01" mainfont: "Apple SD Gothic Neo" # macOS default CJKmainfont: "Apple SD Gothic Neo" geometry: "margin=0.85in" fontsize: 11pt linestretch: 1.25 colorlinks: true ---
For Linux/CI, use Noto Sans CJK KR; on Windows, use Malgun Gothic. The render script auto-detects the default per OS.
bashpython scripts/infer_colwidths.py input.md > input.colwidths.md
The script:
max(len(header), max(len(cell))) (CJK = 2 cells, ASCII = 1).Override per-table via attribute: {tbl-colwidths="[20,40,40]"} after caption — passes through unchanged.
bashbash scripts/render_pdf.sh -i input.colwidths.md -o output.pdf
Or one-shot:
bashbash scripts/render_pdf.sh -i input.md -o output.pdf --infer-colwidths
xelatex silently drops any character the chosen font does not cover — the PDF renders with the glyph simply missing, no error or warning. Academic markdown routinely carries glyphs a default Latin font misses: transition arrows (→ ↑ ↓), math operators (− ≤ ≥ ± √ ∪ × ≈ ≠), stats Greek (κ μ σ β), bullets/marks (• ★ ✓), and CJK. Scan the source first so a silent drop is caught before it ships:
bashpython3 scripts/scan_glyph_coverage.py input.md --strict # real cmap check when you have the font file + fonttools: python3 scripts/scan_glyph_coverage.py input.md --font "/path/to/body.otf" --strict
It groups the risky glyphs by class (advisory), or — with --font + fonttools — reports which are genuinely absent from the font's cmap. If risky glyphs are present, ensure mainfont/CJKmainfont cover them (a CJK-capable font such as Apple SD Gothic Neo / Noto Sans CJK usually covers arrows + Hangul but can still miss the true-minus − U+2212 and ★). The DOCX is authoritative; the PDF is a convenience copy — never let a PDF render drop a glyph the document needs.
Open the PDF. Check:
Starter markdown in templates/ (English default; a Korean variant *_ko.md ships alongside each):
anchor-doc.md — Q&A gridproposal-cover.md — research-proposal cover pagebriefing-handout.md — meeting brief (1-page)reference-table.md — comparison-table formatEach template marks slots with a <!-- TODO: --> marker.
| Anti-pattern | Consequence | |---|---| | Equal dash split (\|---\|---\|---\|) | A column with only a short label gets the same width → cramped data columns | | CJKmainfont not set | Hangul falls back to Times New Roman (broken Latin glyphs or blanks) | | Change history / version (e.g. v3.2.2) / PI attribution exposed in a circulation PDF | Confuses the first recipient; leaks internal information | | Quarto tbl-colwidths for PDF | PDF regression in Quarto 1.4+ — trust HTML only |
scripts/render_pdf.sh — pandoc + xelatex wrapper, OS font detectionscripts/infer_colwidths.py — auto-generates pipe-table separator dash ratiosscripts/check_deps.sh — checks for pandoc / xelatex / CJK fonttemplates/ — 4 starters (English) + their *_ko.md Korean variantsreferences/pandoc_korean_cheatsheet.md — collection of frontmatter patterns (Korean-PDF reference)references/known_pitfalls.md — em-dash line breaks, smart quotes, etc. (Korean-PDF reference)retype a number from prose, and do not carry one forward from an earlier draft — a table that was correct in v3 is not evidence it is correct in v4.
/manage-refs separately — this skill does not handle bib..docx or .eml aco-author sent) unmodified as its own artifact. The PDF is a derivative, not a replacement, and the next round is diffed against that source. If the source was itself AI-drafted by a collaborator, treat every number, denominator, and author-year in it as unverified: re-derive each from the underlying paper or analysis output before it reaches the PDF.
Some passages in this skill cite a path of the form ~/.claude/rules/<name>.md. Those are the maintainer's personal global rules, kept outside this repository. They are not shipped with this skill and will not exist on your machine; they appear only as provenance for where a convention came from. If one of them looks like it is standing in for an instruction you actually need, that is a bug — please open an issue, because the instruction belongs here.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 34,353 | 10,965 | -68% | 1 | 1 | 0% | 6,275 | 4,232 | -33% | 0 | 0 | — |
case-02 | fail→fail | 28,093 | 5,407 | -81% | 1 | 1 | 0% | 4,822 | 2,499 | -48% | 0 | 0 | — |
case-03 | fail→fail | 42,238 | 6,773 | -84% | 1 | 1 | 0% | 8,252 | 2,631 | -68% | 0 | 0 | — |
case-04 | fail→pass | 20,606 | 8,114 | -61% | 1 | 1 | 0% | 3,348 | 3,836 | +15% | 0 | 0 | — |
case-05 | fail→pass | 17,498 | 4,990 | -71% | 1 | 1 | 0% | 2,972 | 3,109 | +5% | 0 | 0 | — |
case-06 | fail→pass | 9,282 | 4,828 | -48% | 1 | 1 | 0% | 1,418 | 3,102 | +119% | 0 | 0 | — |
case-19 | fail→pass | 22,614 | 3,158 | -86% | 1 | 1 | 0% | 3,508 | 2,843 | -19% | 0 | 0 | — |
case-07 | fail→pass | 7,155 | 4,100 | -43% | 1 | 1 | 0% | 1,186 | 2,924 | +147% | 0 | 0 | — |
case-08 | fail→pass | 16,844 | 9,038 | -46% | 1 | 1 | 0% | 2,645 | 3,992 | +51% | 0 | 0 | — |
case-09 | fail→fail | 13,656 | 8,130 | -40% | 1 | 1 | 0% | 2,165 | 3,696 | +71% | 0 | 0 | — |
case-10 | pass→pass | 11,148 | 4,519 | -59% | 1 | 1 | 0% | 2,029 | 3,160 | +56% | 0 | 0 | — |
case-20 | fail→pass | 7,694 | 2,697 | -65% | 1 | 1 | 0% | 1,256 | 2,732 | +118% | 0 | 0 | — |
case-11 | pass→pass | 11,072 | 4,962 | -55% | 1 | 1 | 0% | 1,932 | 3,198 | +66% | 0 | 0 | — |
case-12 | fail→pass | 8,730 | 5,555 | -36% | 1 | 1 | 0% | 1,518 | 3,294 | +117% | 0 | 0 | — |
case-13 | fail→pass | 15,150 | 2,687 | -82% | 1 | 1 | 0% | 2,495 | 2,744 | +10% | 0 | 0 | — |
case-14 | fail→pass | 18,346 | 4,223 | -77% | 1 | 1 | 0% | 3,211 | 2,992 | -7% | 0 | 0 | — |
case-15 | fail→pass | 13,128 | 5,353 | -59% | 1 | 1 | 0% | 2,488 | 3,127 | +26% | 0 | 0 | — |
case-16 | fail→pass | 9,027 | 2,602 | -71% | 1 | 1 | 0% | 1,624 | 2,739 | +69% | 0 | 0 | — |
case-17 | fail→pass | 15,838 | 4,383 | -72% | 1 | 1 | 0% | 3,031 | 3,118 | +3% | 0 | 0 | — |
case-18 | fail→pass | 16,785 | 3,593 | -79% | 1 | 1 | 0% | 2,441 | 2,961 | +21% | 0 | 0 | — |
case-21 | pass→pass | 6,384 | 4,556 | -29% | 1 | 1 | 0% | 1,159 | 3,094 | +167% | 0 | 0 | — |
case-22 | fail→pass | 9,361 | 2,580 | -72% | 1 | 1 | 0% | 1,996 | 2,731 | +37% | 0 | 0 | — |
case-23 | pass→pass | 13,536 | 9,158 | -32% | 1 | 1 | 0% | 2,493 | 4,070 | +63% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted, and 21 counted toward the lift figure. The other 2 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +70 percentage points is the difference between those two pass rates over the 21 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.