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brand-guidelines

Extract a brand's visual and verbal identity into an applicable guideline kit — tokens, voice rules, and do/don't pairs — then apply it consistently to any artifact

Install / Use

npx skills add mohitagw15856/pm-claude-skills --skill brand-guidelines

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

88/100

Supported Platforms

Universal

Our assessment of brand-guidelines

brand-guidelines scores 88/100 on our quality scale, 437th of 1,144 Content & Media skills we index (top 39%).

Its SKILL.md is 6.5 KB long, well organised into 10 sections with 1 code example: a thorough specification that gives an agent plenty to work with.

With 1,396 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
17/20
Description
15/15
Adoption
13/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 8 days ago, so brand-guidelines is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

brand-guidelines compared with similar skills

All 4 of these similar skills score higher than brand-guidelines; compare them before choosing.

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brand-guidelines (this skill)by mohitagw15856881.4k8d agoSKILL.md
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algorithmic-artby anthropics100177.9k10d agoSKILL.md
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Frequently asked questions

How do I install brand-guidelines?
Run npx skills add mohitagw15856/pm-claude-skills --skill brand-guidelines. The install tabs above show the steps for each supported agent.
Which AI agents does brand-guidelines work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is brand-guidelines safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is brand-guidelines still maintained?
The repository was last updated 8 days ago, so brand-guidelines is actively maintained.

name: brand-guidelines description: "Extract a brand's visual and verbal identity into an applicable guideline kit — tokens, voice rules, and do/don't pairs — then apply it consistently to any artifact. Use when asked to apply brand guidelines to a document/deck/page, to extract a brand kit from existing materials or a website, to keep AI-produced artifacts on-brand, or to write lightweight brand guidelines for a startup. Produces a compact brand kit (visual tokens + voice rules + application examples) and/or an artifact restyled to it. For a creator's personal voice use creator-brand-kit; for building new UI systems use frontend-design."

Brand Guidelines Skill

Brand consistency dies at the edges — the sales deck someone made at midnight, the AI-generated one-pager in default blue. This skill works both directions: extract a usable kit from whatever brand evidence exists (a website, a deck, a logo folder), and apply it so any artifact — deck, doc, landing page, social card — looks and sounds like it came from the same company.

What This Skill Produces

  • A brand kit: visual tokens (color roles with hex, type choices, spacing/radius feel, logo rules) + voice rules (register, vocabulary, banned phrases) + do/don't pairs
  • Or an artifact application: the given document/deck/page restyled to the kit, with a conformance note

Required Inputs

Ask for (if not already provided):

  • Mode: extract a kit, apply an existing kit, or both
  • Brand evidence (extract mode): the website URL/screenshots, existing decks, the logo files — 2-3 real artifacts beat a mission statement
  • The artifact and its audience (apply mode): what's being branded and for whom
  • The formality of truth: is there an official guidelines doc this must defer to, or is this creating the de-facto one?

Programmatic Helper

Extract mode says "the exact hex values, not memory". Reading them off a screenshot is memory. Read them off the site:

npx --yes notugly steal example.com        # palette with usage counts, fonts, radii, shadows
npx --yes notugly spec example.com         # the same, as a table you can paste in
npx --yes notugly name "#4f76b6"           # "Hydrangea" — a name a stakeholder can argue with

steal parses the real stylesheets and returns each colour with how many times it is used, which is what separates a brand colour from a one-off in a footer. spec adds a measured contrast ratio and an inferred role per colour.

For Apply mode, npx notugly fix "#fg" "#bg" gives the nearest passing colour to the brand's own — same hue, same chroma — which is how you honour rule 3 below without abandoning the palette.

Deterministic, zero dependencies, no model call. It reads the stylesheets a browser fetches on first load, so it sees what a browser sees and not what JavaScript adds later — a partial sample, honestly labelled.

Extract Method

  1. Mine artifacts, not aspirations. Pull from what the brand actually ships: the exact hex values (from the site's CSS/screenshots, not memory), the real font stack, how much whitespace they genuinely use, how their headlines are actually written. The "About" page says "bold and human"; the evidence says what that means in practice.
  2. Reduce color to roles with rules. Primary (and its ONE job), neutrals, functional colors — each with hex, and the usage rule that makes it applicable: "primary on CTAs and key numbers only; never as body backgrounds." A palette without usage rules is a paint chip, not a guideline.
  3. Capture type as decisions. Families, the weights actually used, the headline pattern (sentence case? title case? length?), body sizing feel. Note the don'ts observed: no italics anywhere? never centered body text?
  4. Extract voice as mechanics (same discipline as style-fingerprint): sentence length feel, person ("we" vs product-name-as-subject), jargon stance, the phrases that recur, the phrases that would never appear. Write 3 do/don't pairs from real copy.
  5. Logo hygiene minimum: clearspace, minimum size, what backgrounds it sits on, the misuses to ban (stretching, recoloring, effects).

Apply Method

  1. Token-map the artifact first — inventory its current colors/fonts/spacings, then map each to the kit's equivalent. Wholesale mapping beats spot-fixing (spot-fixing produces the half-branded artifact, which reads worse than unbranded).
  2. Apply voice, not just paint — retitle headings in the brand's headline pattern, sweep for banned phrases, adjust register. A perfectly-colored deck in the wrong voice still feels off-brand.
  3. Respect the hierarchy of the artifact — branding never overrides legibility: contrast checks still bind (measure them — npx notugly fix returns the nearest passing colour in the same hue rather than making you abandon the brand colour), dense tables stay functional; the brand's job is recognition, not decoration.
  4. Note conformance honestly — what was applied, what couldn't be (font unavailable → declared substitute), what needs a human/designer call.

Output Format

The kit (extract mode):

Brand kit: [company] — extracted from [evidence] on [date]

Color roles: [role → hex → the usage rule] · Type: [families/weights/patterns + observed don'ts] Spacing & shape feel: [airy/dense · radius/shadow character] Logo rules: [clearspace/min size/backgrounds/banned misuses] Voice: [mechanics + 3 do/don't pairs from real copy] Confidence notes: [what was inferred vs evidenced]

The application (apply mode): the restyled artifact + a conformance note (mapped / substituted / needs-designer).

Quality Checks

  • [ ] Every color carries a hex AND a usage rule — no paint-chip palettes
  • [ ] Voice rules are mechanics with real-copy examples, not adjectives
  • [ ] Extracted values trace to actual artifacts (site CSS, real decks) — nothing from memory of the brand
  • [ ] Applications map tokens wholesale, and include the voice pass
  • [ ] Contrast/legibility survived the branding — checked, not assumed

Anti-Patterns

  • [ ] Do not extract a brand from its mission statement — mine what they ship, not what they say
  • [ ] Do not guess hex values from memory of a famous brand — screenshot/CSS or it's fiction
  • [ ] Do not spot-fix ("make the title teal") — half-branded reads worse than unbranded; map wholesale
  • [ ] Do not brand at the cost of legibility — a low-contrast on-brand slide fails both jobs
  • [ ] Do not ship a kit without usage rules — a palette and a font list is where inconsistency comes FROM

Related Skills

View on GitHub
GitHub Stars1.4k
CategoryContent
Updated8d ago
Forks249

Languages

HTML

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions