prompt-to-asset: Skill for Claude Code

.claude/skills/vectorize/SKILL.md

vectorize is a skill for Claude Code from MohamedAbdallah-14/prompt-to-asset. It costs 47 tokens per session (864 once invoked), scanned A, original, MIT.

A tool for turning raster images, such as PNGs, into SVG files. It offers hosted or local methods for multi-color images, single-color artwork, logos, illustrations, and line art.

In plain words
What is it for?
Use it to convert logos, illustrations, icon packs, typography, and line drawings into editable SVG artwork.
Why use it?
It removes the need to manually redraw bitmap images as scalable vector graphics, while reducing stray details and optimizing the resulting SVG.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is MohamedAbdallah-14/prompt-to-asset's own configuration. It tells Claude Code how to work on prompt-to-asset itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything prompt-to-asset configures →

Part of the prompt-to-asset plugin — 13 skills, 1 MCP server shipped together

Reuse

Borrowing it

Nothing to install: this file belongs to MohamedAbdallah-14/prompt-to-asset. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/MohamedAbdallah-14/prompt-to-asset/main/.claude/skills/vectorize/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/MohamedAbdallah-14/prompt-to-asset

Made for: Claude Code.

Or install prompt-to-asset, the plugin that ships this one along with the rest of its 13 skills, 1 MCP server.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for vectorize

README.md
[![agentmods](https://agentmods.dev/badge/skills/mohamedabdallah-14/prompt-to-asset/vectorize/github.svg)](https://agentmods.dev/skills/mohamedabdallah-14/prompt-to-asset/vectorize)
Your own site
<a href="https://agentmods.dev/skills/mohamedabdallah-14/prompt-to-asset/vectorize"><img src="https://agentmods.dev/badge/skills/mohamedabdallah-14/prompt-to-asset/vectorize/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for vectorize

Your own site · 80×15
<a href="https://agentmods.dev/skills/mohamedabdallah-14/prompt-to-asset/vectorize"><img src="https://agentmods.dev/badge/skills/mohamedabdallah-14/prompt-to-asset/vectorize.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 864 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00047 $0.00864
Opus 5 $0.00023 $0.00432
Sonnet 5 $0.00009 $0.00173
Haiku 4.5 $0.00005 $0.00086

Measured 12d ago against content hash c22a4bf3aec0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

vectorize scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/vectorize/SKILL.md · 102 lines

How it starts

The opening of the file, as written. The whole thing — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Vectorize

Three paths

1. Recraft /vectorize (hosted, highest quality)

Input: any raster. Output: clean SVG, typically 20–100 paths for a mark, 200–500 for an illustration. Commercial tier only.

const svg = await recraft.vectorize({ image: pngBuffer });

2. vtracer (local, multi-color polygon)

  • Rust binary; npm install vtracer for the Node wrapper.
  • Modes: polygon (recommended for logos), spline (smoother curves), pixel (blocky).
  • Color count controlled upstream via K-means quantization before vectorization.
pipeline:
  raster 1024²
  → BiRefNet matte (alpha the background)
  → K-means LAB 6-color palette
  → vtracer --mode polygon --filter-speckle 4 --color-precision 6
  → SVGO (conservative preset)

3. potrace (local, 1-bit)

  • Classical Stan Ford vectorizer; binary output only (no color).
  • Best for: icon packs (single-color), typography work, line art.
  • Multi-color workaround: separate each color into its own 1-bit layer, vectorize each, stack SVG <g>s.
pipeline:
  raster 1024²
  → BiRefNet matte
  → per-color mask (binary threshold per palette entry)
  → potrace per mask → <g> wrapper
  → combine into single SVG
  → SVGO

Choosing the path

Use case Path
Budget available, one-shot quality Recraft vectorize
Multi-color logo, local vtracer (polygon mode)
Single-color icon pack potrace
Photorealistic illustration → vector don't — keep as PNG/WebP. Vectorization of photoreal is lossy noise.

Path-count quality signal

After vectorization, count <path> elements:

  • ≤40 paths → clean, production-ready mark.
  • 40–200 paths → likely acceptable; scan for overlapping slivers.
  • >200 paths → probably bad. Either the input has noise (regenerate), too many colors (reduce K-means), or the subject is inappropriate for vectorization (keep as raster).

SVGO configuration

Conservative preset — preserve: viewBox, IDs, classes. Strip: metadata, editor comments, hidden elements.

Read the full file on GitHub · 102 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 102 lines · 47 tokens per session scan A c22a4bf3aec0

Subscribe to this mod's changes

vectorize is a skill published in the GitHub repository MohamedAbdallah-14/prompt-to-asset (19 stars, last pushed yesterday), licensed MIT. It adds 47 tokens to every session and 864 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

skillshare-ui-website-style

Skillshare frontend design system for the React dashboard (ui/) and Docusaurus website (website/). Use this skill whenever you: build or modify a dashboard page or component in ui/src/, style or layout website pages or custom CSS in website/, create new React components for the dashboard, add pages to the dashboard…

runkids/skillshare · 147 tokens

user-research-cookiy

End-to-end user research assistant — qualitative and quantitative. Use this skill whenever the user mentions user research, user interviews, discussion guides, interview guides, research plans, qualitative research, quantitative research, user surveys, survey design, usability studies, participant recruitment…

cookiy-ai/user-research-skill · 154 tokens

figma-connect

Figma-to-code bridge combining Figma MCP server tools with the Code Connect CLI for end-to-end design implementation workflows. Use this skill when implementing UI components from Figma design URLs, publishing Code Connect mappings to Figma Dev Mode, extracting design tokens from Figma variables, setting up Figma Code…

anton-abyzov/vskill · 223 tokens

frontend-design

Create distinctive, production-grade frontend interfaces with visual verification. Use this skill when the user asks to build web components, pages, landing pages, dashboards, React/Vue/Svelte components, HTML/CSS layouts, or any web UI that needs to look polished. Also activates when styling, beautifying…

anton-abyzov/vskill · 133 tokens

excalidraw-mcp

Build Excalidraw diagrams through the official Excalidraw MCP and turn the same source into a real .excalidraw file on disk or an Obsidian .excalidraw.md drawing. Use whenever the user says "use Excalidraw MCP", asks to create/draw/visualize a diagram, flowchart, architecture, sequence, swimlane, mind map or ER…

anton-abyzov/vskill · 146 tokens

unship

Compare agent-made alternatives in a local browser preview with Unship. Use for comparison setup, iteration, Canvas, selection, cleanup, and Unship installation or update troubleshooting.

mbenhard/unship · 37 tokens