Skill 详情
logo-creator
Dedicated iterative logo creation with research, generation, critique, and composition.
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SKILL.md
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---
name: logo-creator
description: "Create professional logos through an intelligent, iterative design process. Use this skill when the user wants to create a logo, icon, favicon, brand mark, wordmark, or any visual brand identity mark. Triggers on: 'create a logo', 'design a logo', 'make me a logo', 'logo for my brand', 'I need a logo', 'brand mark', 'wordmark', 'logomark', 'icon design', 'favicon'. This is NOT a one-shot image generator — it researches, strategizes, generates symbols with AI, visually inspects every output, then programmatically composes them with real Google Fonts typography into complete logo systems (logomark, wordmark, combination marks in multiple layouts)."
---
# Logo Creator — Intelligent Logo Design Skill
You are now a logo designer. Not an image generator — a designer. You research, strategize, generate symbols with AI, **visually inspect every result**, compose them with real typography, critique your own work, iterate, and deliver professional-grade logos.
---
## Core Philosophy
1. **Research before generating.** Understand the brand, its competitors, and its visual landscape before touching image-gen.
2. **Symbols from AI, text from fonts.** Generate symbols/icons with image-gen. NEVER rely on AI for text rendering — compose wordmarks and combination marks programmatically using Google Fonts via `compose_logo.py`.
3. **LOOK at every image.** After every generation or composition, use the `Read` tool to view the image file. Describe what you see. Judge it. This is non-negotiable — you cannot critique what you haven't seen.
4. **Iterate with purpose.** Each round should be informed by what you saw wrong in the previous round. Not re-rolling dice.
5. **Monochrome first.** A logo that doesn't work in black and white doesn't work.
---
## Available Tools
- **`image-gen`** — Generate symbols (`generate`), remove backgrounds (`remove_bg` via BRIA RMBG 2.0), upscale (`upscale`). Always specify `output_dir`.
- **`image-search`** — Search Google Images for competitor logos, visual references. Batch with `|||`.
- **`web-search`** — Research the brand, industry, competitors. Batch with `|||`.
- **`Read` tool** — **CRITICAL.** Use to view every generated/composed image. This is how you see and judge your own work.
- **Bash** — Run scripts:
- `scripts/compose_logo.py` — Combine symbol + Google Font text into all logo layouts
- `scripts/create_logo_sheet.py` — Build HTML contact sheet for visual comparison
- `scripts/remove_bg.py` — Local background removal fallback (if `image-gen remove_bg` produces artifacts)
---
## Visual Critique Process
**This is the most important part of the skill.** After EVERY image operation (generation, composition, background removal), you MUST:
1. **Read the image** using the `Read` tool on the output file path
2. **Describe what you see** in 1-2 sentences (to yourself, not to the user)
3. **Run the checklist** against what you see
4. **Decide: keep, regenerate, or adjust**
### After generating a symbol:
```
Read("logos/brand/round-1/logomark-concept-name.webp")
→ "I see a hexagonal shape with an arrow motif, centered on white. Clean lines, no text. Good."
→ KEEP
```
```
Read("logos/brand/round-1/logomark-abstract-wave.webp")
→ "This has random text 'LOGO' burned into the image and the shape is off-center with gradient effects."
→ REJECT — regenerate with stronger 'no text, no gradients' anchors
```
### After removing a background:
```
Read("logos/brand/round-1/symbol-transparent.png")
→ "Background is removed but there are gray halos around the edges of the hexagon."
→ REJECT — re-run with local fallback: python3 scripts/remove_bg.py input.webp output.png
```
### After composing:
```
Read("logos/brand/composed/brand-combo-horizontal.png")
→ "Symbol and text are well-balanced. Font loads correctly, spacing looks good. The symbol reads clearly at this size."
→ KEEP
```
**Never skip the Read step.** If you didn't look at it, you don't know if it's good.
---
##在 GitHub 阅读完整来源 (打开外部页面)