svg-precision

Generate structurally correct SVGs from a strict JSON spec (scene graph), then validate and optionally render a PNG preview.

Fast path

1. Turn the user request into a Spec JSON (use templates in references/spec.md).
2. Build the SVG:
   • python scripts/svg_cli.py build spec.json out.svg
3. Validate:
   • python scripts/svg_cli.py validate out.svg
4. (Optional) Render a PNG preview (requires CairoSVG):
   • python scripts/svg_cli.py render out.svg out.png --scale 2

Spec design rules (for accuracy)

• Always set canvas.viewBox and explicit canvas.width/canvas.height.
• Prefer absolute coordinates; use transforms only when they reduce complexity.
• Keep numbers sane: no NaN/inf; round to 3-4 decimals.
• Put reusable items in defs (markers, gradients, clipPaths) and reference by id.
• For predictable results across viewers, avoid exotic filters unless required.
• Text varies by fonts/viewers. If you need pixel-identical results, treat text as a risk and prefer shapes.

Using the bundled scripts

CLI

• python scripts/svg_cli.py build <spec.json> <out.svg>
• python scripts/svg_cli.py validate <svg>
• python scripts/svg_cli.py render <svg> <out.png> [--scale N]
• python scripts/svg_cli.py diff <a.svg> <b.svg> <diff.png> [--scale N] (renders + image-diffs)

As a library (in Python)

from svg_skill import build_svg, validate_svg
svg_text = build_svg(spec_dict)
report = validate_svg(svg_text)

When the request is vague

1. Identify the kind of SVG: icon / diagram / chart / UI / technical.
2. Pick a template from references/spec.md and fill in concrete numbers.
3. If dimensions are unknown, choose defaults that match the domain:
   • icons: 24×24 or 32×32
   • UI mockups: 1440×900 or 390×844 (mobile)
   • charts: 800×450
   • diagrams: 1200×800
   • technical drawings: specify units (mm/in) and scale

References

• references/spec.md – schema + ready-to-copy templates per SVG type
• references/recipes.md – layout and styling patterns that render consistently