Recently, I created a new Logo Skill with quite impressive results: https://github.com/s1dashu/ip-as-logo-skill

The background: I recently noticed that products like grok bot, Coze, Workbuddy, Doubao, Kiro, and others are using their product’s IP character directly as the logo. This approach results in extremely high logo recognizability and strengthens IP memory. I thought it was a great idea.

Therefore, all my recent products have a corresponding cute little IP character, and I use the IP directly as the logo. As I worked on more products with this vibe, this skill gradually took shape.

The core principles of this skill are:

1. Logo First, IP Second: First and foremost, ensure it is a simple, clear, and easily recognizable logo. The cute IP character comes second, avoiding a complex illustrative feel.
2. Minimalist Composition: Retain only the most recognizable outlines and facial features. Use as few shapes as possible in the design so it remains clear when scaled down.
3. Rounded, Bold Lines: Avoid sharp corners, thin lines, and sharp structures to make the character appear more friendly and stable, and more suitable as an App icon.
4. Flat-first with Subtle Skeuomorphic Depth: The design remains primarily flat, with only very subtle shadows, indents, and light variations to enhance texture without becoming a heavy 3D icon.
5. Restrained Color System: Support for single-color or dual-color IPs; typically, the IP itself uses no more than two colors. Combined with a solid background, the entire logo is controlled within a maximum of three main colors.
6. High-Ratio Character Composition: The IP character emerges from the bottom-left or bottom-right corner, occupying a large proportion of the frame; personality and memorability are established through simple eyes, mouth, and posture.

In one sentence: Compress a cute little IP into a refined product logo.

s1dashu/ip-as-logo-skill

Source: https://github.com/s1dashu/ip-as-logo-skill

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, oversized 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 (https://ipaslogo.com), a searchable library backed by Cloudflare R2 and Supabase.

IP as Logo showcase

Don’t have Codex, Doubao, Coze, or Workbuddy? Visit our website (https://ipaslogo.com) to download ready-made logos for free. Every logo is free for commercial use.

What it guides

• One dominant silhouette built from roughly 4–7 large basic shapes
• Three semantic colors by default: two IP base colors plus one background color
• Three proposed directions followed by six independently generated candidates after user approval
• Familiar, broadly appealing animals as the default open-ended subject; objects, machines, fantasy artifacts, and obscure creatures require a clear product reason
• Context-aware, clearly separated subject and background colors with barely-there neo-skeuomorphic depth, described without percentages or prescribed gradient and shading formulas
• Thick, rounded forms without sharp or fragile details
• A 75–85% close crop that visibly peeks or rises from the lower-left or lower-right, with paired identifying features preserved
• Extreme simplification, cute baby-like appeal, and removal of nonessential lines and details
• One named solid background color filling the square, without image-mode language in the generation prompt
• Image-only generation prompts that never reveal logo, brand-mark, app-icon, or icon-asset use
• One-pass batch generation that preserves and delivers every returned image without filtering or automatic retries

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. This skill only supports agents with built-in image-generation capabilities that can return generated images as assets.

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. When the user selects one direction, the skill generates six controlled variants of that direction. If the user rejects the proposed quantity or distribution, their replacement instructions take precedence.

Compatible agents may generate the six candidates in parallel with subagents up to the runtime’s available concurrency, using additional waves when needed. Codex can use ImageGen when available; other agent environments may use any configured image generator. If no generator is available, the skill asks the user to provide or enable one instead of pretending that an image was generated. 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 favors clearly chromatic but restrained backgrounds rather than neon color or muddy gray. 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