Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add neonwatty/logo-designer-skill --skill logo-designergit clone --depth 1 https://github.com/neonwatty/logo-designer-skillWrote 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.
[](https://agentmods.dev/skills/neonwatty/logo-designer-skill/logo-designer)<a href="https://agentmods.dev/skills/neonwatty/logo-designer-skill/logo-designer"><img src="https://agentmods.dev/badge/skills/neonwatty/logo-designer-skill/logo-designer/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.
<a href="https://agentmods.dev/skills/neonwatty/logo-designer-skill/logo-designer"><img src="https://agentmods.dev/badge/skills/neonwatty/logo-designer-skill/logo-designer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket warn
- Snyk fail
- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00061 | $0.04975 |
| Opus 5 | $0.00030 | $0.02488 |
| Sonnet 5 | $0.00012 | $0.00995 |
| Haiku 4.5 | $0.00006 | $0.00498 |
Grade A, and why
logo-designer 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 431 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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"
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 431 lines · 61 tokens per session scan A 6707eb0c6fdd
logo-designer is a skill published in the GitHub repository neonwatty/logo-designer-skill (85 stars, last pushed today), licensed MIT. It adds 61 tokens to every session and 4,975 once invoked, about $0.0003 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.
Other skills, from other repositories
ip-as-logo
Generate extremely simple, cute, personified square character images with rounded heavy forms, two purposeful character colors, one solid background color, and a dominant lower-corner composition. Use when creating an animal, creature, robot, ghost, plant, object, or other character image, including when the agent…
sketch
Recognize and revise concrete sketches to discover a form when descriptions cannot settle intent. Type: (FitUnrecognized, Hybrid, SKETCH-RECOGNIZE-CYCLE, FormIntentSeed) → RecognizedForm.
xiaohongshu-cover
An AI cover-planning tool for Xiaohongshu, a Chinese social platform for lifestyle and product content. It studies popular covers in a topic area and produces three cover concepts with examples and image-generation prompts.
generate-logo
Generates on-brand, editable SVG logo assets — wordmark, monogram, and favicon — from the active brand profile, reusing its exact palette and heading font. Vector output needs no account, key, or network. Use when a user asks for a logo, wordmark, icon, monogram, or favicon. Trigger with "make a logo", "generate a…
create-svg-icon
Design new linear or filled SVG icons and cohesive icon sets through a mandatory raster-first workflow. Use when Codex must invent an icon concept, create branded UI icons, make matching navigation or feature icons, or extend an existing icon family. Always generate PNG concepts with ImageGen first, then invoke the…
pn-image-creator
Questionnaire-driven image creation for high-quality PNG or SVG. Always grounds prompts in pn-cinematography-lighting and pn-image-prompt-engineering (camera, lighting, visual style). Gates on user confirmation before generation. Use with Cursor image generation or SVG per pn-svg-creator.