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Papper

Write in Markdown. Submit in Word.

Papper is a DOCX-first academic writing workflow built for the AI era. AI tools are already great at drafting, revising, and restructuring Markdown. The problem is that many journals, editors, and collaborators still expect .docx. Papper bridges that gap: you keep the clarity and version-control friendliness of Markdown, while generating submission-ready Word documents when it is time to deliver.

Why This Exists

Markdown has become a very natural writing format for research teams, especially when AI is part of the drafting loop. It is easier to generate, review, diff, and refine than LaTeX for many authors. LaTeX is still powerful, but it is not always the most approachable tool for collaborators who mainly need to write and revise. Typst is promising, but it is not yet the default format most journals ask for.

DOCX, however, is still the format a lot of publishers, editors, and co-authors want.

Papper is built around that reality:

• Write the manuscript in Markdown.
• Keep sources easy for humans and AI to edit.
• Generate Word-first output for submission.
• Preserve the pieces academic writing actually needs: citations, equations, tables, figures, cross-references, and reviewer replies.

Why Papper

Papper is not just a generic Pandoc wrapper. It is a manuscript workflow with opinionated support for the annoying parts of real submission work.

• DOCX-first workflow: the primary target is a polished Word manuscript, not DOCX as an afterthought.
• AI-friendly authoring: Markdown is easier for LLMs to generate and easier for humans to review in Git.
• One-command project bootstrap: papper init creates a reusable paper workspace with manuscript files, style metadata, references, and agent guidance.
• Submission-oriented post-processing: Papper applies format-specific cleanup and formatting after Pandoc runs.
• Reviewer reply support: build response letters as DOCX or TXT, while resolving manuscript references and citations.
• Managed Pandoc tools: if pandoc or pandoc-crossref are missing, Papper can install project-local copies under .pmt/tools.
• Optional HTML, LaTeX, and JSON output: keep a Markdown-centered workflow without giving up other export targets.

What You Get

• Manuscript scaffolding with papper init
• Environment checks with papper doctor
• Project-local tool setup with papper setup
• DOCX, LaTeX, and JSON builds with papper build
• Reviewer reply builds with papper build-reply
• Cross-references for figures, tables, equations, and sections
• CSL-based citations
• Reference DOCX support for Word styling
• DOCX post-processing for author blocks, table behavior, styles, and line-number-related workflows
• Tab-layout equation paragraphs automatically use Para Equation, based on Body Text, with 0.5 line spacing after and single line spacing. To apply only this step to an existing DOCX in place, run uv run python -m pandoc_manuscript.docx.postprocess.para_equation_style path/to/file.docx (add --no-save for a dry run). The style's center and right tab stops use half and all of the first DOCX section's writable width (page width minus left/right margins). Direct paragraph tab stops are removed so equations inherit the style's positions; rerun the step after changing page margins.
• SVG handling and DOCX fallbacks for figures that Word does not handle well
• Cross-platform MathType-compatible OLE/WMF equations, with an optional native MathType comparison path on Windows

Quick Start

Prerequisites

Install these tools first:

1. uv for running the CLI and Python environment
2. pandoc 3.0+ and pandoc-crossref
3. For line-number source workflows, Windows requires Microsoft Word; other platforms can use soffice.
4. Optional: MathType on Windows only if you select rust-sdk, set-data, auto, or both; the default rust path is self-contained

Papper requires Pandoc 3.8 or newer. Older or unusable pandoc executables on PATH are ignored; Papper downloads a managed project-local copy into .pmt/tools instead. Missing or unusable pandoc-crossref executables are also installed automatically. Downloads and executable installation use temporary files followed by atomic replacement, so an interrupted build can be rerun. Invalid cached archives are discarded and downloaded again once; unusable managed executables are reinstalled. Bundled Python filters, including the compatibility to_mathbfit filter, run with Papper's Python interpreter and its installed dependencies. On Windows, Papper puts that interpreter first on Pandoc's PATH and runs the Python filters directly, including for manuscript projects on UNC network paths.

Tool downloads automatically use HTTPS_PROXY (or https_proxy) when set, otherwise the configured Windows/macOS system HTTP/HTTPS proxy, and otherwise a direct connection. This applies to both GitHub release metadata and archive downloads during papper build docx, papper setup, and papper init --setup. On Windows, enable your proxy application's system proxy option before building; no extra Papper setting is needed. Papper logs [TOOLS] Using system proxy for downloads. when it selects that route. An explicit HTTPS_PROXY takes precedence over the system setting. PAC scripts and automatic proxy discovery are not evaluated by this downloader.

Rough Python Compatibility Check

If you just want a quick syntax-level check against the project's minimum Python target, use Ruff:

uvx ruff check .

This is only a rough version-compatibility check. It can catch syntax that does not fit the configured Python target, but it does not prove runtime compatibility.

Create Your First Project

uvx --from papper papper init my-paper
cd my-paper
papper doctor
papper build docx

For a Chinese manuscript and reviewer-reply starter, use papper init my-paper --lang zh-cn.

To initialize the manuscript project in the current directory, omit the target directory:

papper init

That produces:

output/docx/manuscript.docx

If you prefer installing the tool once:

uv tool install --upgrade papper
papper init my-paper

After each papper invocation, Papper reads its cached PyPI update status and prints an upgrade hint when one is available. A silent background worker refreshes that cache at most once every hour, so commands do not wait for network I/O. Upgrade an installed Papper tool with:

uv tool upgrade papper

Upgrade from the previous package name

PyPI treats papper as a new project name. To move an existing tool installation from pandoc-manuscript-template, remove the old tool and install Papper:

uv tool uninstall pandoc-manuscript-template
uv tool install papper

The pmt command remains available as a compatibility alias. Existing manuscript projects keep their .pmt working directory and PMT_* settings.

Typical Workflow

# Create a new manuscript project
papper init my-paper --setup

# Check dependencies and project files
papper doctor

# Build the main manuscript
papper build docx

# Build a Chinese-primary DOCX with localized cross-references and chapter-numbered figures/tables
papper build docx --lang zh-cn

# Build another Markdown file explicitly
papper build docx paper.md -o build/paper.docx

# Build one standalone HTML file with embedded resources
papper build html -o build/paper.html

# Build a reviewer reply
papper build-reply reply.md --reply-manuscript manuscript.md -o output/docx/reply.docx

HTML builds use the shared Pandoc filters for Chinese nested numbering and !<!/!^! table-cell merge markers, plus HTML post-processing for author information. DOCX also uses the shared AST filter for standalone inline-math spacing before Word conversion. The three-line table appearance comes from Pandoc's built-in standalone HTML CSS. A direct Pandoc command needs -s/--standalone to include that CSS; without it, Pandoc writes only an HTML fragment.

Chinese DOCX builds use the bundled GB/T 7714—2015 bilingual numeric CSL by default. An explicit csl in manuscript metadata or style.yml overrides it.

Standout Features

1. Markdown that stays pleasant to edit

Papper leans into plain-text authoring instead of fighting it. Your manuscript remains easy to diff, refactor, prompt into AI tools, and review collaboratively.

2. DOCX output that is actually the point

Many academic writing pipelines treat DOCX as a secondary export. Papper treats it as the main delivery format, with Word-oriented defaults and post-processing built into the workflow.

3. Better fit for real submission tasks

Papper goes beyond "convert Markdown to Word" by helping with the parts that tend to break late in the process:

• reviewer replies
• figure and table references
• equation numbering
• citation formatting
• Word reference documents
• DOCX figure edge cases such as SVG conversion or embedding

4. Friendly to automation without hiding the files

The output is scripted, reproducible, and version-controlled, but the source project still looks like a normal manuscript folder that a researcher can understand quickly.

Documentation Map

• template/.agents/manuscript-syntax.md: manuscript syntax, citations, cross-references, pseudocode, revision markup, and style metadata
• template/manuscript.md: example manuscript content
• AGENTS.md: repository-specific guidance for coding agents

In generated projects, style.yml keeps Papper-owned build settings at the top level and places metadata sent to Pandoc under pandocMetadata. Manuscript YAML overrides only the Pandoc metadata domain.

When Papper Is a Good Fit

Papper is especially useful if:

• you draft heavily with AI and want a format AI handles naturally
• you want Git-friendly manuscript sources instead of editing Word binaries directly
• your target journal still expects DOCX
• you need a repeatable manuscript and reviewer-reply workflow
• you want Pandoc power without forcing every collaborator into a LaTeX-first workflow

Commands at a Glance

papper init [directory]
papper setup
papper doctor
papper build docx
papper build html
papper build latex
papper build json
papper build-reply reply.md -o output/docx/reply.docx
papper clean
papper distclean

Use papper --help to see the full CLI.

Add --verbose to any command, for example papper build docx --verbose, to show detailed debug logs such as complete external command lines. Normal output keeps the main build stages, warnings, and results concise.

Maintainer releases and native build caches

Release with uvx bump-my-version bump patch followed by git push origin main --tags. The Publish to PyPI workflow publishes only on v* tag pushes. Its main builds and manual runs build and verify the same three platform wheels without publishing them.

Changes to either Rust submodule, the native build hook, helper inputs, or the publishing workflow trigger cache warming on main. To warm or refresh caches manually, run Publish to PyPI with Run workflow, selecting main. Complete the first warm-up before creating the next release tag: GitHub allows tags to restore default-branch caches, but not caches saved under other tags. Pushing main and a tag together does not make the tag wait for cache warming; it can use an older main cache and compile any changed dependencies.

The workflow pins Rust to 1.98.0 and caches Cargo downloads and release build outputs separately for Windows, macOS 14, and manylinux 2.28. Cache keys include the toolchain, native lockfiles, submodule revisions, build configuration, and equation preferences, rather than the Python package version. Only successful main builds save caches; tag builds restore them and still run Cargo with --locked, package the wheel, and verify its native libraries.

The wheel builds and ships only the mathtype-rust shared library. Its versioned C ABI handles OLE/MTEF conversion and operation="render_wmf" requests, linking latex2wmf once as a pinned Git dependency. The renderer retains backend, style, font size, and math-font options. The standalone latex2wmf crate and CLI remain available for development; its dynamic library is not shipped.

CI sets CARGO_TARGET_DIR to persist native build artifacts. On Linux this directory and Cargo's download cache live on the host via the container's /host mount, so they survive the manylinux container. Local builds retain their normal per-project target directories unless this environment variable is set. Build logs report elapsed time for each Rust library and the Windows .NET helper. A cold cache or a toolchain change still requires compilation; actual release speedups should be measured after a successful warm-up.

Before saving the Linux cache, the workflow transfers its container-created files to the runner user and checks directory sizes and readability. A lookup after saving requires the exact cache entry to exist remotely; an archive/upload failure therefore fails the warm-up instead of silently leaving future releases uncached.

Acknowledgments

• Pandoc
• pandoc-crossref

Support

• Review the syntax guide in template/.agents/manuscript-syntax.md
• Open an issue with a minimal reproducible example

Typst equation font

Configure style.yml to select an installed OpenType math font:

mathtype: true
mathtypeConversionMethod: rust
mathtypeSvgBackend: typst
mathtypeTypstMathFont: Cambria Math

Bundled math families are XITS Math (the default) and New Computer Modern Math. You can also set mathtypeTypstMathFont: fonts/STIXTwoMath-Regular.otf to load a font file without installing it. Relative paths resolve beside the style file; absolute paths are supported. Accepted files are .otf, .ttf, .ttc, and .otc, and must contain an OpenType math font. Collections select their first math family. When using a custom family name, install it in every build environment. Changing the family or font file contents invalidates the formula preview cache. This controls Typst SVG/WMF previews, not editable MathType OLE font preferences. It has no effect on RaTeX or native MathType previews (set-data / rust-sdk). auto tries native MathType set-data first and falls back directly to rust; both compares both backends, prefers the native MathType result, and uses the Rust result if native conversion fails.

If the mathtype-rust native library reports a formula conversion error, the build warns with the exit code and LaTeX input and continues. The affected formula retains its original Word equation (OMML); other formulas are converted normally. In both and auto modes, conversion tries set-data as each formula is converted when that backend is available. These modes do not run a separate startup probe for the per-formula failure policy. If three consecutive formulas fail with the helper message 由于 Exception.ToString() 失败，因此无法打印异常字符串, PMT treats set-data as unavailable on that computer for the remainder of the current build and uses Rust for subsequent formulas. A successful set-data conversion or a different failure resets the consecutive counter. If all selected backends fail for a formula, its original Word equation is retained. Failed conversions are not cached.