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Brand Dna

skill-thatrebeccarae-claude-marketing-brand-dna · by thatrebeccarae

Extract brand identity from a website URL — voice, colors, typography, imagery, values, and target audience — into a structured brand-profile.json. The profile feeds downstream skills (seo-content-writer, email-composer, frontend-design, pro-deck-builder, cross-platform-audit) for brand-consistent output. Use when the user says brand DNA, brand profile, extract brand, analyze brand, brand voice,…

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Install

$ agentstack add skill-thatrebeccarae-claude-marketing-brand-dna

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

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Declared compatibility

Claude CodeClaude Desktop

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About

Brand DNA — Brand Identity Extractor

Extracts brand identity from a website and produces a structured brand-profile.json that other skills can consume for brand-consistent output.

Install

git clone https://github.com/thatrebeccarae/claude-marketing.git && cp -r claude-marketing/skills/brand-dna ~/.claude/skills/

Quick Reference

| Command | What It Does | |---------|-------------| | "Extract brand DNA from https://example.com" | Full extraction → brand-profile.json | | "Quick brand profile for https://example.com" | Homepage-only extraction (faster, lower confidence) |

Zero Dependencies

This skill uses only the WebFetch tool — no Python scripts, no Playwright, no external APIs. It works anywhere Claude Code runs.

Extraction Process

Step 1: Collect URL

If the user hasn't provided a URL, ask: > "What website URL should I analyze? (e.g., https://yoursite.com)"

Step 2: Fetch Pages

Use the WebFetch tool to retrieve page content. For each URL, request:

  • All visible text content
  • Full contents of `` blocks
  • Inline style= attributes
  • ` tags (especially og:image, description`)
  • Google Fonts @import URLs
  • Any `` tags referencing external stylesheets

Fetch order:

  1. Homepage (``)
  2. About page — try /about, then /about-us, then /our-story
  3. Product/Services page — try /products, then /product, then /services

Quick mode: If the user requests a quick extraction, fetch homepage only — skip pages 2 and 3.

If a secondary page returns 404 or redirects to homepage, continue with fewer pages and note reduced confidence.

Step 3: Extract Brand Elements

Colors
  • Primary color: Most prominent brand color from CSS background-color on .hero, .btn-primary, header, or og:image dominant color
  • Secondary colors: Supporting palette from CTAs, accents, borders
  • Background/text: body background-color and color
  • Forbidden: Infer from brand positioning (e.g., competitor colors if identifiable)
  • Dark mode detection: If body background is #333 or darker, swap background/text values

CSS targets: background-color, color, border-color on body, header, .hero, .btn, .cta, h1, h2

Typography
  • Google Fonts: Extract from @import url(https://fonts.googleapis.com/css2?family=...) — parse font name from URL
  • CSS font-family: Check h1, h2, body, .headline declarations
  • Fallback: If no Google Fonts detected, set headingfont to null and bodyfont to "system-ui"
Voice (1-10 scale per axis)

Analyze hero headline, subheadline, about page intro, and CTA button text:

| Signal | Axis | Direction | |--------|------|-----------| | Uses "you/your" frequently | formalcasual | +2 toward casual | | Technical jargon, industry terms | expertaccessible | -2 toward expert | | Short punchy sentences (≤8 words) | boldsubtle | +2 toward bold | | Data, stats, percentages in hero | rationalemotional | -2 toward rational | | "Transform", "revolutionize", "disrupt" | traditionalinnovative | +2 toward innovative | | Customer testimonials lead | rationalemotional | +2 toward emotional | | "Trusted by X companies", awards | traditionalinnovative | -1 toward traditional | | Humor, wordplay, casual phrasing | playfulserious | +2 toward playful | | Formal language, third person | playful_serious | -2 toward serious |

Start each axis at 5 (neutral) and adjust based on signals found.

Descriptors: Choose 3-5 adjectives that capture the overall voice tone. These should complement the numerical scores, not repeat them.

Imagery
  • Style: Professional photography, illustration, flat design, 3D renders, or mixed
  • Subjects: What appears in hero images and product shots (people, products, abstract, data)
  • Composition: Clean/minimal, busy/editorial, dark/dramatic, light/airy
  • Forbidden elements: Infer from industry (healthcare → no unqualified medical claims imagery; B2B → no cheesy stock photos)
Aesthetic
  • Mood keywords: 3 adjectives describing the visual mood (e.g., "trustworthy", "modern", "premium")
  • Texture: minimal, textured, or mixed
  • Negative space: generous, moderate, or dense
Brand Values

Extract from about page, mission statement, or footer. Look for repeated themes. Choose 3-5 core values.

Target Audience

Infer from copy, pricing signals, and positioning:

  • Age range: Estimate from visual design, language complexity, and product type
  • Profession: Who the product/service is for
  • Pain points: What problems the brand addresses (from hero copy and feature descriptions)
  • Aspirations: What the audience wants to achieve (from benefit-oriented copy)

Step 4: Build brand-profile.json

Construct the JSON following the schema in REFERENCE.md precisely. Use null for any field that cannot be confidently extracted — never guess.

Step 5: Write and Confirm

Write brand-profile.json to the current working directory.

Display a summary:

Brand DNA extracted → brand-profile.json

  Brand: [brand_name]
  Voice: [descriptor 1], [descriptor 2], [descriptor 3]
  Primary Color: [hex]
  Typography: [heading_font] / [body_font]
  Audience: [age_range], [profession]

This profile can be consumed by:
  - seo-content-writer (voice matching)
  - email-composer (tone calibration)
  - frontend-design (visual identity)
  - pro-deck-builder (brand colors/fonts)
  - cross-platform-audit (brand consistency checks)

Limitations

  • Sparse sites: <200 words of body text produce lower-confidence profiles. Note this in output.
  • SPA/React sites: JavaScript-rendered content may not be fully captured by WebFetch. Note this if detected.
  • Multi-brand enterprises: Creates one profile per URL. Run separately for each brand.
  • CSS-in-JS: Modern React/Next.js sites may not have extractable CSS. Use og:image analysis as fallback.

How to Use This Skill

Ask questions like:

  • "Extract the brand DNA from https://example.com"
  • "Build a brand profile for my client's website"
  • "Analyze the brand voice and colors of https://competitor.com"
  • "Quick brand profile — homepage only — for https://example.com"
  • "What's the brand identity of this website?"

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.