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 seb1n/awesome-ai-agent-skills --skill logo-designgit clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skillsWrote 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/seb1n/awesome-ai-agent-skills/logo-design)<a href="https://agentmods.dev/skills/seb1n/awesome-ai-agent-skills/logo-design"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/logo-design/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/seb1n/awesome-ai-agent-skills/logo-design"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/logo-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00042 | $0.01865 |
| Opus 5 | $0.00021 | $0.00932 |
| Sonnet 5 | $0.00008 | $0.00373 |
| Haiku 4.5 | $0.00004 | $0.00186 |
Grade A, and why
logo-design 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 13d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- Logo Design — 98% identical, 4 lines differ
How it starts
The opening of the file, as written. The whole thing — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Logo Design
This skill enables the agent to guide the complete logo design process — from creative brief through final deliverables. The agent produces design specifications covering symbol concepts, color palettes, typography selections, and file format requirements. It applies core design principles (simplicity, scalability, memorability, versatility) to ensure logos work across digital screens, print media, favicons, and social avatars.
Workflow
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Gather Brand Context: Collect the brand name, industry, target audience, competitors, and personality attributes (e.g., "modern and approachable" vs. "luxurious and exclusive"). Ask about existing brand colors, fonts, or visual assets that must be incorporated. Determine where the logo will primarily appear — website, mobile app, packaging, signage — since this shapes format and scalability requirements.
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Define the Design Brief: Synthesize the gathered information into a structured design brief that includes brand values, visual direction keywords, color preferences, and mandatory constraints. Specify the logo types needed: icon/symbol mark, wordmark (logotype), combination mark, and favicon/app icon. List required file formats and sizes upfront so deliverables are clear.
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Generate Concept Directions: Produce 2-3 distinct concept directions, each with a rationale explaining how it reflects the brand. For each direction, describe the symbol or letterform treatment, the color palette (primary, secondary, accent with hex codes), and the recommended typeface pairing. Explain the visual metaphor or design logic behind each concept.
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Refine the Selected Concept: Once the user selects a direction, iterate on it. Adjust proportions, letter-spacing, icon weight, and color balance. Test the design at multiple sizes — a 16x16 favicon, a 48x48 app icon, a 200px web header, and a large-format print version — to confirm legibility and visual impact at every scale.
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Produce Final Deliverables: Output the complete file specification: SVG (vector master), PNG at 512x512, 256x256, 128x128, and 64x64, plus a 16x16 and 32x32 ICO favicon. Provide light-background and dark-background versions, a monochrome version, and a minimum-size guideline. Include a one-page brand mark usage guide covering clear space, minimum size, and color placement rules.
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.
- 13d ago First seen · 100 lines · 42 tokens per session scan A a1f12dfe44cb
logo-design is a skill published in the GitHub repository seb1n/awesome-ai-agent-skills (179 stars, last pushed 1mo ago), licensed MIT. It adds 42 tokens to every session and 1,865 once invoked, about $0.0002 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.
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