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standalone packages

Packages

Sprezzature has three layers. The skills (the SKILL.md files an agent reads) stay in the main repository. The deterministic tools each graduate into their own pip-installable package, so you can use one without cloning the whole stack. A local runtime lets the tools run offline against a local model.

Each package is BSD-3-Clause, local-first, and independently versioned. They are not on PyPI yet, so install straight from GitHub.

Deterministic tools

sprezzature-figures

Figures

91 chart types, Vega-first with an SVG escape hatch, plus the Ralph Eyeball Loop, explainability, and causal DAGs.

pip install git+https://github.com/warith-harchaoui/sprezzature-figures
Repository →

sprezzature-colors

Colors

WCAG contrast auditing with OKLCH-neighbour fixes, colour-vision-deficiency simulation, a curated palette, and Tailwind export.

pip install git+https://github.com/warith-harchaoui/sprezzature-colors
Repository →

sprezzature-accessibility

Accessibility

A static HTML accessibility linter: source-decidable WCAG/WAI rules, no browser, no runtime DOM. A fast pre-commit gate.

pip install git+https://github.com/warith-harchaoui/sprezzature-accessibility
Repository →

sprezzature-cli-gui

CLI → web GUI

Auto-generate a single-file HTML GUI from any Python CLI: it introspects argparse, Click, or Typer, with no build step.

pip install git+https://github.com/warith-harchaoui/sprezzature-cli-gui
Repository →

sprezzature-ux-laws

Laws of UX

A static Laws-of-UX auditor for HTML: Hick, Miller, Fitts, Jakob, Tesler and more, decidable from source.

pip install git+https://github.com/warith-harchaoui/sprezzature-ux-laws
Repository →

sprezzature-audio

Audio

Local captions (whisper.cpp), speaker diarization and who-is-who, narration and translation. ML backends are optional extras.

pip install git+https://github.com/warith-harchaoui/sprezzature-audio
Repository →

Runtime & engine

best-engine-ai-helper

Engine picker & local runtime

Detect the machine, pick a model from a catalog, and validate a local LLM / VLM before the skills lean on it. Every skill's LLM/VLM call routes through its chat abstraction: a pluggable backend (Ollama, OpenAI-compatible, LangChain), the Ralph loop, and the writing pipeline.

pip install git+https://github.com/warith-harchaoui/best-engine-ai-helper
Repository →

Looking for the agent skills instead? The SKILL.md layer ships together as the skills bundle on the Getting started section.