Logo Designer logo

Logo Designer

Community
neonwatty
logo-designer

Design and iterate on logos using SVG. Use this skill when the user asks to "create a logo", "design a logo", "make me a logo", "iterate on this logo", "logo for my project", or discusses logo design, branding icons, or wordmarks.

Overview

Publisherneonwatty
Repositorylogo-designer-skill
Skill namelogo-designer
Stars
187
Forks
24
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by neonwatty on GitHub. Read the source before you install it.

Installation

Install the Logo Designer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/neonwatty/logo-designer-skill/tree/main/skills/logo-designer
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/neonwatty/logo-designer-skill.git /tmp/logo-designer-skill
mkdir -p .claude/skills
cp -r /tmp/logo-designer-skill/skills/logo-designer .claude/skills/logo-designer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Logo Designer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Logo Designer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Logo Designer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Logo Designer

Design and iterate on logos using SVG. Generates side-by-side previews and exports to PNG at standard sizes.

Phase 1: Interview

Before generating anything, gather context and ask the user what they need.

Step 1: Gather context automatically

If the user points to a repo, URL, or existing project:

  • Read the README, package.json, CSS/config files, and any existing branding
  • Extract: project name, purpose, tech stack, color palette, design language, fonts
  • Summarize what you found before asking questions — this avoids asking things you already know

If the user just says "design a logo" with no project context, skip to Step 2.

Step 2: Ask structured questions

Use the AskUserQuestion tool to ask these questions. Batch related questions together (up to 4 per call) and skip any question already answered by the context gathered in Step 1 or by the user's initial message.

Question 1 — Format:

question: "What format do you need?"
header: "Format"
options:
  - label: "Icon only (512x512)"
    description: "Square icon, works for favicons, app icons, social avatars"
  - label: "Wordmark only"
    description: "Text logo, 1024x512"
  - label: "Combination mark"
    description: "Icon + text together, 1024x512"

Question 2 — Style direction:

question: "What style direction?"
header: "Style"
options:
  - label: "Minimal / geometric"
    description: "Clean lines, simple shapes, modern feel"
  - label: "Playful / hand-drawn"
    description: "Friendly, casual, organic shapes"
  - label: "Bold / corporate"
    description: "Strong, professional, high contrast"
  - label: "Match existing app style"
    description: "I'll extract the design language from your project"

Question 3 — Color preferences:

question: "Any color preferences?"
header: "Colors"
options:
  - label: "Use project colors"
    description: "I'll pull colors from your existing design system"
  - label: "Surprise me"
    description: "I'll pick a palette that fits the vibe"
  - label: "I have specific colors"
    description: "I'll ask you for them"

Question 4 — Output size (only if the user mentioned a specific platform):

question: "Any specific size requirements?"
header: "Size"
options:
  - label: "Standard sizes"
    description: "16, 32, 48, 192, 512, 1024, 2048px — covers most uses"
  - label: "Custom size needed"
    description: "I'll ask for the exact dimensions"

Adapting to context

  • User points to a repo: Gather context first, then ask only format + style (colors are likely known).
  • User says "design a logo for X": Ask format, style, and colors together.
  • User gives detailed description: Skip everything already covered, ask only what's missing.
  • User says "just make something": Use sensible defaults (icon only, minimal, surprise me) and go straight to Phase 2.

Move to Phase 2 once you have enough to generate distinct concepts.

SVG Conventions

When generating SVG logos, follow these rules:

  • viewBox sizing — Always use viewBox="0 0 W H" without fixed width/height attributes. Use 512x512 for icons, 1024x512 for wordmarks/combination marks.
  • Self-contained — No external fonts, images, or <use> references to other files. Everything inline.
  • Text handling — Use widely available system fonts (Arial, Helvetica, Georgia, etc.) or convert text to <path> elements. When using system fonts, always include a generic fallback (e.g., font-family="Helvetica, Arial, sans-serif").
  • Meaningful groups — Wrap logical sections in <g> elements with descriptive IDs: id="icon", id="wordmark", id="tagline". This makes iteration easier when the user says "make the icon bigger" or "change the wordmark color".
  • Flat fills by default — Use solid fill colors. Only use gradients (<linearGradient>, <radialGradient>) when the user requests them or the style clearly calls for it.
  • Small-size legibility — Logos must work at 16-32px (favicons). Prefer solid fills over thin strokes, avoid fine details that disappear at small sizes, and use stroke-width of 6+ for any outlines that need to remain visible. Test this mentally: if a detail won't survive being 32px wide, simplify it.
  • Clean markup — No unnecessary transforms, no empty groups, no default namespace clutter. Keep the SVG readable.

Phase 2: Explore

Generate 3-5 distinct SVG logo concepts. Each concept should take a meaningfully different creative direction — vary the icon metaphor, typography style, layout, or overall aesthetic. Do not generate minor variations of the same idea.

Parallel generation

Use the Task tool to generate all concepts in parallel. This is significantly faster than writing them sequentially.

  1. Create the logos/concepts/ directory first
  2. Dispatch one Task agent per concept, all in the same message so they run concurrently. Each agent should:
    • Receive the full design brief (format, style, colors, viewBox, SVG conventions)
    • Be assigned a specific creative direction (e.g., "geometric letterform", "abstract symbol", "mascot-based")
    • Write its SVG to a specific file path (e.g., logos/concepts/concept-1.svg)
    • Use subagent_type: "general-purpose" and mode: "bypassPermissions"
  3. After all agents complete, generate logos/preview.html and present the results

Example dispatch pattern (all in one message):

Task 1: "Write logos/concepts/concept-1.svg — geometric letterform using [colors]. viewBox 512x512. Self-contained SVG, no external fonts. [full SVG conventions]."

Task 2: "Write logos/concepts/concept-2.svg — abstract symbol using [colors]. viewBox 512x512. Self-contained SVG, no external fonts. [full SVG conventions]."

Task 3: "Write logos/concepts/concept-3.svg — mascot-based icon using [colors]. viewBox 512x512. Self-contained SVG, no external fonts. [full SVG conventions]."

Each agent prompt must include: the full SVG conventions from this skill, the target file path, the specific creative direction, and all relevant context (project name, colors, style preferences). Agents do not share context — give each one everything it needs.

File output

logos/
├── concepts/
│   ├── concept-1.svg
│   ├── concept-2.svg
│   ├── concept-3.svg
│   └── ... (up to concept-5.svg)
└── preview.html

After all parallel agents complete:

  1. Generate logos/preview.html using the preview template below
  2. Tell the user to open logos/preview.html in their browser
  3. Briefly describe each concept (1 sentence each) so the user can match descriptions to visuals
  4. Ask: "Which direction do you want to explore? Pick a number, or describe what you like/dislike across them."

Preview HTML Template

When generating logos/preview.html, use this template. Replace {{CARDS}} with one card per SVG file. Set {{PHASE}} to "Concepts" during explore or "Iterations" during refine.

html
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Logo Preview — {{PHASE}}</title>
<style>
  * { margin: 0; padding: 0; box-sizing: border-box; }
  body {
    font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, sans-serif;
    padding: 2rem;
    transition: background-color 0.3s, color 0.3s;
  }
  body.light { background: #f5f5f5; color: #333; }
  body.dark { background: #1a1a1a; color: #eee; }
  .header {
    display: flex;
    justify-content: space-between;
    align-items: center;
    margin-bottom: 2rem;
  }
  h1 { font-size: 1.5rem; font-weight: 600; }
  .toggle {
    padding: 0.5rem 1rem;
    border: 1px solid currentColor;
    border-radius: 6px;
    background: transparent;
    color: inherit;
    cursor: pointer;
    font-size: 0.875rem;
  }
  .grid {
    display: grid;
    grid-template-columns: repeat(auto-fill, minmax(280px, 1fr));
    gap: 1.5rem;
  }
  .card {
    border: 1px solid rgba(128, 128, 128, 0.3);
    border-radius: 12px;
    overflow: hidden;
  }
  .card-img {
    display: flex;
    align-items: center;
    justify-content: center;
    padding: 2rem;
    min-height: 240px;
  }
  body.light .card-img { background: #fff; }
  body.dark .card-img { background: #2a2a2a; }
  .card-img img {
    max-width: 100%;
    max-height: 200px;
  }
  .card-label {
    padding: 0.75rem 1rem;
    font-size: 0.875rem;
    font-weight: 500;
    border-top: 1px solid rgba(128, 128, 128, 0.3);
  }
  body.light .card-label { background: #fafafa; }
  body.dark .card-label { background: #222; }
</style>
</head>
<body class="light">
  <div class="header">
    <h1>Logo Preview — {{PHASE}}</h1>
    <button class="toggle" onclick="document.body.classList.toggle('dark'); document.body.classList.toggle('light'); this.textContent = document.body.classList.contains('dark') ? '☀️ Light' : '🌙 Dark';">🌙 Dark</button>
  </div>
  <div class="grid">
    {{CARDS}}
  </div>
</body>
</html>
Favicon size check strip

During Phase 3 (Refine), add a "Favicon Size Check" section below the iteration grid. This renders each iteration at 64px, 32px, and 16px so the user can spot legibility issues early. Use this HTML pattern:

html
<h2>Favicon Size Check</h2>
<div style="display:flex;gap:2rem;flex-wrap:wrap;align-items:end;">
  <!-- Repeat for each iteration -->
  <div style="display:flex;flex-direction:column;align-items:center;gap:0.5rem;">
    <div style="font-size:0.8rem;font-weight:500;">{{LABEL}}</div>
    <div style="display:flex;gap:1rem;align-items:end;">
      <div><img src="{{FAVICON_PATH}}" width="64" height="64"><div style="font-size:0.75rem;opacity:0.6;">64px</div></div>
      <div><img src="{{FAVICON_PATH}}" width="32" height="32"><div style="font-size:0.75rem;opacity:0.6;">32px</div></div>
      <div><img src="{{FAVICON_PATH}}" width="16" height="16"><div style="font-size:0.75rem;opacity:0.6;">16px</div></div>
    </div>
  </div>
</div>

For icon-only logos, {{FAVICON_PATH}} is the iteration path. For combination marks, create a standalone square SVG from the meaningful #icon group and use its path for {{FAVICON_PATH}}. Never squeeze the full horizontal wordmark into the square favicon cells. If details disappear at 32px, suggest simplifying (remove fine details, thicken strokes, drop decorative elements).

Each {{CARDS}} entry is:

html
<div class="card">
  <div class="card-img">
    <img src="{{PATH}}" alt="{{LABEL}}">
  </div>
  <div class="card-label">{{LABEL}}</div>
</div>

Where {{PATH}} is the relative path from logos/ (e.g., concepts/concept-1.svg or iterations/iteration-3.svg) and {{LABEL}} is the filename without extension (e.g., "concept-1" or "iteration-3").

During explore, show all concepts. During refine, show all iterations (most recent first).

Phase 3: Refine

Once the user picks a concept direction, iterate on it.

Single vs. batch iterations

Single iteration — When the user gives specific feedback ("make the icon bigger", "change the blue to green"), apply the change directly and write the next iteration SVG yourself.

Batch variations — When exploring multiple directions at once ("try different color palettes", "show me 5 variations of the eye shape", "experiment with bar count"), use the Task tool to generate variations in parallel, just like Phase 2:

  1. Dispatch one Task agent per variation, all in the same message
  2. Each agent receives: the base SVG content (copy the full SVG inline in the prompt), the specific variation to apply, the target file path, and the full SVG conventions
  3. After all agents complete, regenerate logos/preview.html and present the results

Example batch dispatch:

Task 1: "Take this base SVG [full SVG content] and create a variation with a warm color palette (reds, oranges, yellows). Write to logos/iterations/iteration-5.svg."

Task 2: "Take this base SVG [full SVG content] and create a variation with a cool color palette (blues, teals, purples). Write to logos/iterations/iteration-6.svg."

Task 3: "Take this base SVG [full SVG content] and create a variation with a monochrome palette (grays + one accent). Write to logos/iterations/iteration-7.svg."

Use subagent_type: "general-purpose" and mode: "bypassPermissions" for each agent. Always include the full base SVG content in each agent's prompt — agents do not share context.

File output

logos/
├── iterations/
│   ├── iteration-1.svg    # First refinement (based on chosen concept)
│   ├── iteration-2.svg
│   └── ...
└── preview.html           # Regenerated to show iterations
  1. Copy the chosen concept as the starting point — save the first refinement as logos/iterations/iteration-1.svg
  2. Apply the user's feedback and save each new version with an incrementing number
  3. Regenerate logos/preview.html after each iteration, showing all iterations (most recent first) so the user can compare
  4. Tell the user to refresh their browser after each iteration
  5. After each iteration, briefly describe what changed and ask for next feedback

Iteration tips

  • If the user says "go back to iteration N", use that as the new base
  • If the user wants to compare specific iterations, mention which filenames to look at in the preview
  • Keep SVG structure consistent across iterations (same group IDs) so the user can track what changed
  • Use parallel agents for batch exploration (3+ variations), sequential writes for single tweaks
  • Check small-size legibility — After generating iterations, include the favicon size check strip in the preview. If thin strokes vanish at 32px, proactively suggest thickening them. If fine details (clocks, sparkles, thin icons) become unreadable, suggest removing or simplifying them. This saves iteration cycles.
  • When the user is satisfied, move to Phase 4

Optional Lineage review (explicit opt-in only)

Standalone SVG files and logos/preview.html are always the default. Do not look for, start, or connect to Lineage merely because it may be installed or a runtime descriptor exists. Use Lineage only after the user explicitly asks for canvas review and provides the Lineage checkout or adapter command.

For an explicit review, keep the handoff one-way and public-boundary-only. Run the Lineage adapter with an explicit artifact, selector, and target, then pipe its single versioned JSON receipt to the bundled stdin-only handoff:

bash
npm --prefix /absolute/path/to/lineage-logo --silent run agent:submit -- \
  --mode replace \
  --artifact /absolute/path/to/logos/iterations/iteration-2.svg \
  --selector '#logo' \
  --target-name logo | \
node <path-to-skill>/scripts/lineage-handoff.mjs \
  --logos /absolute/path/to/logos

The handoff never starts or locates Lineage and accepts no token, API origin, artifact argument, or connection context. It consumes only the adapter receipt on stdin. On an accepted receipt, it atomically creates the next collision-safe logos/iterations/iteration-N.svg, rereads the published bytes, verifies them, and prints a metadata-only receipt containing iterationPath, bytes, and sha256. File data and supported directory metadata are synchronized before that continuation receipt is emitted. Pre-transaction invalid or unavailable adapter receipts contain no fabricated transaction, source-path, or revision identity and remain terminally consumable by the same handoff. Continue refinement only from that exact iterationPath, then regenerate logos/preview.html so the verified iteration remains visible in the normal workflow.

For reverted, rejected, stale, unavailable, conflict, timeout, or invalid receipts, follow the printed terminal guidance and do not create or reserve an iteration. The producer waits through temporary editor disconnections so a reconnected canvas cannot accept the same proposal after this handoff has stopped listening. If an authoritative accepted receipt cannot be persisted, exit 27 preserves its transaction identity, byte count, and hash. Fix the local storage problem and rerun the same adapter command with that transaction ID and the same artifact; do not create a new transaction. Never automatically resubmit after timeout or conflict. A new submission must be an explicit user-directed action after checking the current canvas state. If Lineage reports that its local server was replaced during a provisional acceptance, do not infer a terminal result and do not continue from browser memory. Inspect the locked canvas and use its explicit Restore previous document recovery action; only after that exact transaction is resolved may the user explicitly start another handoff.

Phase 4: Export

When the user says "export", "I'm happy with this", "this is the one", or similar:

  1. Identify the final iteration SVG (ask the user to confirm which one if ambiguous)
  2. Create the logos/export/ directory
  3. Copy the final SVG to logos/export/logo.svg. For a combination mark, also create a standalone square logos/export/icon.svg from its meaningful #icon group. Preserve the icon's appearance and give it a tight square viewBox; do not include the wordmark.
  4. Run the bundled export script to generate PNGs. Passing an SVG that is already at its destination is supported:
bash
bash <path-to-skill>/scripts/export.sh logos/export/logo.svg logos/export/

For a combination mark, pass the standalone icon as the optional third argument:

bash
bash <path-to-skill>/scripts/export.sh logos/export/logo.svg logos/export/ logos/export/icon.svg

The script produces:

  • logo-16.png
  • logo-32.png
  • logo-48.png
  • logo-192.png
  • logo-512.png
  • logo-1024.png
  • logo-2048.png

When an icon SVG is provided, the script also preserves icon.svg and produces the matching icon-16.png through icon-2048.png family. Use the icon-* assets for favicons and app icons; use the logo-* assets where the complete combination mark belongs.

  1. Report the results: list all exported files with their sizes
  2. If the export script fails (no conversion tool found), tell the user:

    "No SVG-to-PNG converter found. Install one of: npm install -g @aspect-build/resvg, or install Inkscape, or install librsvg. Then run export again."

Export script location

The export script is bundled with this skill at scripts/export.sh relative to the SKILL.md file. Use the skill's directory path to locate it.

Phase 5: Repo Integration (optional)

If the user asks to commit the logo to a project repo or create a PR:

  1. Identify target files — Check the repo for existing icon/logo files: public/favicon.svg, public/favicon.ico, public/pwa-*.png, public/apple-touch-icon.png, assets/logo.svg, ios/.../AppIcon.appiconset/, public/manifest.json, etc.
  2. Clone and branch — Clone the repo (or use the existing checkout), create a branch like chore/new-logo
  3. Replace files — Copy the final SVG as the favicon/logo. Generate platform-specific sizes:
    • favicon.ico — 48px (use ImageMagick convert or magick)
    • apple-touch-icon.png — 180px
    • pwa-192x192.png — 192px
    • pwa-512x512.png — 512px
    • iOS AppIcon-512@2x.png — 1024px
    • Only replace files that already exist in the repo — don't add new ones the project doesn't use
  4. Commit and PR — Commit with a message like chore: replace logo with new [description], push, and create a PR with a summary of what was updated

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Logo Designer AI skill do?

Design and iterate on logos using SVG. Use this skill when the user asks to "create a logo", "design a logo", "make me a logo", "iterate on this logo", "logo for my project", or discusses logo design, branding icons, or wordmarks.

Why use Logo Designer on TypingMind?

Because you install it once and use it with any model. Logo Designer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Logo Designer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/neonwatty/logo-designer-skill/tree/main/skills/logo-designer. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Logo Designer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Logo Designer?

As many as you like. As long as a model supports skills, you can use Logo Designer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Logo Designer AI skill free?

Yes. It is published on GitHub by neonwatty under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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