Ferrari-design-analysis

Ferrari-design-analysis is a skill for Claude Code from skillmds/skillmd. It costs 199 tokens per session (6,609 once invoked), scanned A, original, MIT.

A visual design guide based on Ferrari's marketing style, including its colors, fonts, layout spacing, and use of cinematic car photography. It describes how these elements are arranged across marketing pages.

In plain words
What is it for?
Use it to design Ferrari-style marketing pages, including hero sections, headlines, buttons, pricing areas, and vehicle or racing content.
Why use it?
It gives an agent concrete visual rules to follow when recreating or extending this specific brand style.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the brand-identity-kit plugin — 13 skills shipped together

Good fit Use it to design Ferrari-style marketing pages, including hero sections, headlines, buttons, pricing areas, and vehicle or racing content.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/skillmds/skillmd/ferrari-design-analysis
Install

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.

Any agent
npx skills add skillmds/skillmd --skill ferrari-design-analysis
Clone the repo
git clone --depth 1 https://github.com/skillmds/skillmd

Made for: Claude Code.

Or install brand-identity-kit, the plugin that ships this one along with the rest of its 13 skills.

Wrote 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.

agentmods badge for Ferrari-design-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/skillmds/skillmd/ferrari-design-analysis/github.svg)](https://agentmods.dev/skills/skillmds/skillmd/ferrari-design-analysis)
Your own site
<a href="https://agentmods.dev/skills/skillmds/skillmd/ferrari-design-analysis"><img src="https://agentmods.dev/badge/skills/skillmds/skillmd/ferrari-design-analysis/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.

agentmods 80×15 button for Ferrari-design-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/skillmds/skillmd/ferrari-design-analysis"><img src="https://agentmods.dev/badge/skills/skillmds/skillmd/ferrari-design-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 199 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,609 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00199 $0.06609
Opus 5.5 $0.00080 $0.02644
Sonnet 5 $0.00040 $0.01322
Haiku 4.5 $0.00020 $0.00661

Measured 4d ago against content hash d06737ca16e6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-23, from the pricing page.

Security

Grade A, and why

Ferrari-design-analysis 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 4d 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.

plugins/brand-identity-kit/skills/ferrari-design-analysis/SKILL.md · 532 lines

How it starts

The opening of the file, as written. The whole thing — 532 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Overview

Ferrari's marketing site reads as cinematic editorial — closer to a luxury-magazine spread than a typical car-OEM site. The base canvas is near-black ({colors.canvas} — #181818) holding pure white display type; white-canvas bands appear only inside specific editorial contexts (preowned listings, pricing tables, dealer surfaces). The single brand voltage is Rosso Corsa ({colors.primary} — #da291c), the iconic Ferrari racing red, used scarcely on primary CTAs, the Cavallino mark, and Formula 1 race-position highlights.

Type runs FerrariSans as the single sans family at modest weights — display 500, body 400. CTA labels render in uppercase with generous tracking (1.1-1.4px). The brand never uses bold display copy.

The brand's strongest visual signature is the full-bleed cinematic hero photograph — top-of-page imagery shows car photography, model details, or trackside livery without any chrome competing with it. Headlines float over the bottom of the photo or sit in a tight band beneath. Spacing follows the explicit 8px token ladder: xxxs 4 / xxs 8 / xs 16 / sm 24 / md 32 / lg 48 / xl 64 / xxl 96 / super 128.

Key Characteristics:

  • Single accent: {colors.primary} (Rosso Corsa #da291c) for primary CTAs, the Cavallino, F1 race-position highlights. Used scarcely.
  • Near-black canvas (#181818) — never pure black. White-canvas bands only inside editorial contexts.
  • Single sans family: FerrariSans across every text role.
  • Display weight stays at 500 — never bold.
  • CTA labels render uppercase with 1.4px tracking.
  • Sharp {rounded.none} (0px) corners on every CTA, card, and band — luxury-automotive precision.
  • Full-bleed cinematic hero photography is the page chrome.
  • Explicit 8px spacing token ladder with named scale (xxxs through super).
  • Hairlines + photographic depth — no drop shadow tiers.

Colors

Brand & Accent

  • Rosso Corsa ({colors.primary} — #da291c): The iconic Ferrari racing red. Primary CTA fill, Cavallino mark, F1 driver-position highlights. Used scarcely.
  • Rosso Corsa Active ({colors.primary-active} — #b01e0a): Press state.
  • Rosso Corsa Hover-darker ({colors.primary-hover} — #9d2211): Documented for completeness; per the no-hover policy this is not used in preview HTML.
  • Hypersail Yellow ({colors.accent-yellow-hypersail} — #fff200) + Yellow ({colors.accent-yellow} — #f6e500): Sub-brand accents reserved for the Hypersail sailing program and the global focus-ring color. Not part of the main automotive palette.

Read the full file on GitHub · 532 lines

Files

What ships with it

1 file 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.

Changes

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.

  1. 4d ago First seen · 532 lines · 199 tokens per session scan A d06737ca16e6

Subscribe to this mod's changes

Ferrari-design-analysis is a skill published in the GitHub repository skillmds/skillmd (1 stars, last pushed yesterday), licensed MIT. It adds 199 tokens to every session and 6,609 once invoked, about $0.0008 per session on Opus 5.5. 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 2026-09-19.

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