ip-as-logo-skill README

The project's README from github.com/s1dashu/ip-as-logo-skill. As one markdown file: README.md.

IP as Logo

ip-as-logo is a compact Agent Skill for generating extremely simple, cute, company-ready IP mascots. It prioritizes lovable character appeal, bold rounded silhouettes, strict complexity limits, a dominant lower-corner composition, and a solid named background color.

It follows the open Agent Skills format and is designed to work with any compatible AI agent, rather than being tied to a specific agent product.

You can also browse the free IP as Logo Skill website, a searchable library backed by Cloudflare R2 and Supabase.

IP as Logo showcase

Don't have Codex, Doubao, Coze, or Workbuddy? Visit our website to download ready-made logos for free. Every logo is free for commercial use.

What it guides

Install

Install the complete skill with the Agent Skills CLI:

npx skills@latest add s1dashu/ip-as-logo-skill

The installer detects the repository's root SKILL.md, lets you choose a supported coding agent, and installs the complete ip-as-logo directory, including its supporting assets. Use --global for a personal installation available across projects:

npx skills@latest add s1dashu/ip-as-logo-skill --global

Agent compatibility

Supported agents include Codex, Coze, Doubao, YouMind, Manus, Gemini Apps, and Replit Agent. The agent must have a top-tier image model: preferably GPT Image 2, or Seedance 5.0 Pro, Nano Banana Pro (Gemini Image Pro), or Nano Banana 2 (Gemini Image Flash). If none is available, enable a suitable tool or provide its API key. The skill never falls back to SVG; another image model may be used only with explicit user consent, with no guarantee of equivalent quality.

Use

Ask your AI agent for an IP mascot image, for example:

Create a very simple, cute rounded ghost IP character on a solid deep navy background.

The skill does not ask for a color-mode choice by default. Every default candidate uses three semantic colors: two IP base colors plus one background color. It no longer reserves any fraction of the candidate set for two-color images. A two-color image is generated only when the user explicitly requests it, and then uses background-colored negative space for facial marks rather than introducing a third color.

When the user already names an IP subject, the skill proposes three controlled design treatments of that subject. When the subject is open, it proposes familiar animal mascots first and ties each to a product attribute or brand promise. In open-ended batches, 95–100% of candidates should be familiar animals; non-animal subjects are limited to a small minority with a direct product connection, never used merely to manufacture novelty.

Large batches create variety within commercially plausible animal mascots through species or breed, ear and muzzle proportions, expression, lower-left versus lower-right emergence, crop, silhouette, and secondary color organization. Clocks, locks, industrial tools, measuring instruments, vehicles, abstract machines, fantasy artifacts, and obscure creatures are not default company mascots.

If the skill runs inside a product repository, it inspects relevant read-only context before asking questions. If product context is insufficient, it asks one consolidated round of background questions. Once context is sufficient, it always presents three concise directions and proposes generating six independent images. It proceeds after the user agrees, or immediately when the user has already explicitly authorized six outputs.

When the user accepts all three directions, the default batch contains two variants per direction: A1, A2, B1, B2, C1, and C2. The first variant of each direction emerges from the lower-left and the second from the lower-right. When the user selects one direction, odd-numbered variants use the lower-left and even-numbered variants use the lower-right. This guarantees a three-left, three-right default split. If the user rejects the proposed quantity or distribution, their replacement instructions take precedence.

Every default candidate emerges from the lower-left or lower-right rather than the center or bottom-center and fills roughly 85–95% of the square so the IP remains visually dominant. Bottom or side cropping may strengthen the corner emergence, but the Skill does not prescribe exact edge contact or a fixed crop.

Compatible agents may generate the six candidates in parallel with subagents up to the runtime's available concurrency, using additional waves when needed. The skill checks for a supported top-tier image model before generation and asks the user to enable one or provide its API key when necessary. Every result is a separate full-resolution square asset, never a six-image contact sheet.

When the user does not supply a palette, the skill gently lowers background saturation so the result feels a little more muted and controlled while remaining clearly chromatic, clean, and intentional rather than vivid, gray, or muddy. It keeps the normal design to exactly three semantic colors: two IP base colors plus the background. The generation prompt names the intended solid background color directly and avoids terms such as opaque, alpha, or transparency that may distract the image model from the desired visual result.

Although the project is named ip-as-logo, the prompt sent to the image generator describes only the requested square character image. It never calls the result a logo, brand mark, app icon, or icon asset, and it does not prepend use-case metadata that reveals those purposes.

Generation is intentionally treated as a creative draw. Each requested candidate is generated once and delivered as returned. The skill does not inspect transparency, block outputs, classify candidates as compliant or non-compliant, or automatically retry results because of their background, colors, composition, gradients, shading, or dimensionality. Users can explicitly request another draw or a refinement after reviewing the batch.

Repository structure

SKILL.md
assets/ip-as-logo-wall.webp
README.md
LICENSE

The skill itself intentionally consists of a single instruction document. The repository also includes the showcase image above, but no scripts, style references, or generation dependencies.

Model behavior

Image-generation models are stochastic and may interpret individual constraints differently. The skill preserves and returns every result without validation gates, transparency checks, automatic rejection, automatic retry, or silent repair.

License

MIT

ip-as-logo-skill (s1dashu/ip-as-logo-skill)

creative-tools
Searching Database…

6K ·GitHub
Ip-as-logo-skill
What is this?ip-as-logo is a compact Agent Skill that guides an AI agent to generate extremely simple, cute, company-ready IP mascot logos with a rounded, subtly neo-skeuomorphic style.
Is this an app, or just an instruction file my agent reads?It is a single instruction document (SKILL.md) following the open Agent Skills format, not a standalone app or script bundle; it works with any compatible AI agent rather than one specific product.
How do I install this skill?Run the Agent Skills CLI, which detects the repo's root SKILL.md, lets you pick a supported coding agent, and installs the full ip-as-logo directory with its assets; add --global to make it available across all your projects.
Which agents and image models does it need?It works with Codex, Coze, Doubao, YouMind, Manus, Gemini Apps, or Replit Agent, and the agent needs a top-tier image model such as GPT Image 2, Seedance 5.0 Pro, Nano Banana Pro, or Nano Banana 2 (or an API key for one).
Will it fall back to a vector logo if no good image model is available?No, the skill never produces an SVG fallback; a lower-tier image model may only be used with the user's explicit consent and there is no guarantee of equivalent quality, and generated results are returned as-is without any automatic retries or quality filtering.
What does a default batch of logos look like?By default it produces six independent full-resolution square candidates across three design directions (A1/A2, B1/B2, C1/C2), split evenly between mascots emerging from the lower-left and lower-right corners, each filling 85-95% of the frame with just three semantic colors.
Can I get a mascot logo without any of the supported coding agents?Yes, the project also runs a free IP as Logo Skill website, a searchable library backed by Cloudflare R2 and Supabase, where you can download ready-made logos free for commercial use.
Does it favor animal mascots or will it draw objects and machines?In open-ended requests 95-100% of candidates are familiar animal mascots tied to a product trait; objects, vehicles, tools, or fantasy creatures are only used sparingly when there is a clear product reason.
What are similar projects?logo-design-skill, kid-papercraft, gc-minimal-zine-poster, gathered-scenes-zine-skill, travel-memory-sticker-card, ian-xiaohei-illustrations, photo-abstract-editorial, RuiC-card-skill
Which topics is it in?icon, branding, design-tool, creative-tools, codex-skill, ai-tools, agent-skill, gpt, image-generation, design, prompt-engineering, gemini
Creator
s1dashu
Size
29.1 MB
Stars
6K
Updated
CommitAug 22
Age
1mo
Commits · 90 Days