tokenmoulds 3.1.0

Generate branded Office templates from design tokens

TokenMoulds

Generate branded Office templates from design tokens. Point it at a brand, get publication-quality Word, PowerPoint, Excel, LibreOffice, and Google Workspace templates — with embedded fonts, baseline grids, and OOXML compliance validation.

Install

pip install tokenmoulds

Quick Start

Generate templates from brand inputs:

tokenmoulds --org-id="acme" \
  --font-pair="inter-roboto" \
  --primary-color="#2563EB" \
  --secondary-color="#DC2626" \
  --locale="GB" \
  --brand-tone=0.3 \
  --generate-templates --generate-odf

Or from a DTCG token file:

tokenmoulds --org-id="acme" \
  --tokens-file="design.tokens.json" \
  --generate-templates

What It Does

~30 brand inputs (colors, fonts, tone) produce 4,576 derived design tokens across 11 output formats. Every template ships with:

• WCAG AAA accessible contrast ratios
• Embedded fonts with ODTTF obfuscation
• Baseline grid-snapped typography via modular type scales
• ISO 29500 (OOXML) and ODF schema compliance
• Zero macros — all styling baked into document structure

Output Formats

Format	Extension	Highlights
Word	.dotx	276 themed paragraph, character, and table styles
PowerPoint	.potx	Theme colors, embedded fonts, table styles, layouts
Excel	.xltx	Themed cell styles and number formats
Writer	.ott	110 ODF styles with page geometry
Impress	.otp	ODF presentation template
Calc	.ots	ODF spreadsheet template
Draw	.otg	ODF drawing template
Google Docs	.dotx	Optimized for Google Workspace import
Theme	.thmx	Standalone Office theme package

MCP Server

For AI-assisted document creation via Claude, Cursor, or other MCP clients:

tokenmoulds mcp-server

28 tools for brand extraction, template generation, document creation, validation, and cache management. See the MCP tool catalog.

Python API

from tokenmoulds.pipeline import BuildConfig, build

result = build(BuildConfig(
    org_id="acme",
    output_formats=["potx", "dotx", "xltx"],
    brand_inputs={
        "font_pair": {"sans": "Inter", "serif": "Roboto Slab"},
        "base_colors": {"primary": "#2563EB", "secondary": "#DC2626"},
        "locale": "US",
        "brand_tone": 0.5,
    },
))

for fmt, data in result.artifacts.items():
    open(f"acme.{fmt}", "wb").write(data)

Architecture

TokenMoulds uses a single canonical build pipeline:

Design Tokens → DesignResolutionEngine → DocumentIR → Emitters → Validated Packages

• DTCG pipeline: W3C Design Tokens Community Group format with 5-layer resolution (core/fork/org/group/personal)
• Design engine: Modular type scale, baseline grid, OpenType features, tone/density adaptation
• Document IR: Format-agnostic intermediate representation
• 11 emitters: Each produces a complete, valid package
• Validation: In-process ISO 29500 schema checking via openxml-audit

See ADR 027 for the full convergence story.

Development

git clone https://github.com/BramAlkema/TokenMoulds.git
cd TokenMoulds
python -m venv venv && source venv/bin/activate
pip install -e ".[dev]"
python -m pytest tests/ -v --tb=short   # 1,629 tests

Contributing

See CONTRIBUTING.md for development guidelines, code conventions, and how to submit changes.

Documentation

• Getting Started
• CLI Reference
• MCP Tool Catalog
• Architecture Decisions

License

MIT