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figure-spec

Generate editable SVG diagrams from structured FigureSpec JSON.

Updated Jun 10, 2026
Search Tags:#workflow#architecture#rendering#svg#deterministic#diagram#figure
One-click install
npx skills add https://github.com/xqinag/ARIS-new --skill figure-spec-xqinag
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: figure-spec
Source: https://github.com/xqinag/ARIS-new/tree/main/skills/figure-spec
Command: npx skills add https://github.com/xqinag/ARIS-new --skill figure-spec-xqinag

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires cairosvg, and includes scripts (resource) components.

What problem does it solve?

Automatically convert structured diagram specifications into publication-quality, editable SVGs, removing manual drawing effort.

Core Features & Use Cases

  • Deterministic rendering: identical input always yields the same SVG.
  • Editable vector output: SVG is plain-text and easy to modify by hand or program.
  • No external API: runs locally with a pure Python renderer and optional local tooling.
  • Schema validation: validates inputs and provides clear error messages.
  • Use Case: Produce architecture, workflow, and topology figures for papers and documentation.

Quick Start

Render a FigureSpec JSON to produce an editable SVG diagram.

Frequently Asked Questions about figure-spec

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate deterministic SVG diagrams from structured specifications?▼

Deterministic SVG diagrams are generated by converting structured FigureSpec JSON input through a local Python renderer. Identical input always yields the exact same SVG output, ensuring reproducible publication-quality visuals without manual drawing effort.

Can I render architecture and workflow diagrams locally without an external API?▼

Architecture and workflow diagrams can be rendered locally without an external API using a pure Python renderer with a strict no-network policy. The process operates entirely offline, applying schema validation to ensure correct structured input before generating SVG and PNG previews.

Does the renderer support PNG previews in addition to editable SVG output?▼

PNG previews are supported alongside editable SVG output via the included Python renderer and the cairosvg dependency. The SVG output remains plain-text and fully editable by hand or programmatically, while PNG previews provide quick visual validation of the diagram.

What is the best way to create reproducible topology diagrams for publication?▼

Reproducible topology diagrams are best created by defining node positions, connections, and grouping in structured FigureSpec JSON. This method guarantees that semantic meaning is preserved across edits and the local renderer applies optional edge styling for publication-quality figures.

Do I need cairosvg to validate diagram specs and output SVG files?▼

Cairosvg is required to generate PNG previews from the rendered SVG files. The core rendering engine uses a pure Python renderer to produce the editable SVG and validate the FigureSpec JSON schema, while cairosvg specifically handles the rasterized preview output.

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