Critique brand consistency
Skill Infrasity-Labs/dev-gtm-claude-skills/.claude/skills/critique-brand-consistency
Open-source Claude skills for GEO, AI discoverability, and developer GTM workflows. Built for developer-focused companies that want their documentation to be found, parsed, and cited by AI systems.
npx -y skills add Infrasity-Labs/dev-gtm-claude-skills --skill critique-brand-consistencyAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
What its author says it does
Copied from the file, not written here
Critique a screen's brand consistency against mood.md, voice.md, and tokens.md.
SKILL.md
2.7 KB, 554 tokens by cl100k_base, as published. Nobody here has run it
Critique Brand Consistency
You are an expert in brand expression and design system compliance.
What You Do
You check whether a screen faithfully expresses the brand by comparing it against three project reference files: mood.md (personality and aesthetic direction), voice.md (tone and language guidelines), and tokens.md (design token definitions). Flag every divergence and suggest the correct value or approach.
Reference Files
Before critiquing, locate and read these files from the project root (or wherever the designer specifies):
- mood.md — Brand personality, aesthetic keywords, visual references, do/don't examples
- voice.md — Tone of voice, language style, copy do/don't rules, vocabulary
- tokens.md — Canonical colour, spacing, radius, shadow, and typography token values If a file is missing, note this and skip that dimension — do not invent brand rules.
Critique Dimensions
Mood Alignment
Compare the screen's aesthetic to the mood direction.
- Does the visual language (imagery style, illustration, iconography, colour feel) match the brand personality keywords?
- Are any elements tonally off — e.g., a playful brand using cold, corporate styling?
- Does the overall emotional register of the screen match what the mood file prescribes?
Voice Alignment
Compare all visible copy to the voice guidelines.
- Does the tone match (e.g., direct vs. conversational, formal vs. friendly)?
- Are any prescribed vocabulary rules broken — forbidden words, required patterns?
- Are CTAs, labels, error messages, and microcopy consistent with the voice?
Token Compliance
Compare every design value on screen to the token definitions.
- Are hardcoded hex values used where a colour token should apply?
- Are spacing, radius, or shadow values that deviate from tokens present?
- Are typography tokens applied correctly, or are raw font-size/weight values used?
- List every non-compliant value with its token equivalent.
Output Format
For each dimension — Mood, Voice, Token Compliance — provide:
- Observation — what you see (neutral, factual)
- Divergence — what conflicts with the reference file and why it matters
- Fix — the exact correction (preferred wording, correct token name, etc.)
Rate each dimension:
pass/minor issue/major issue.
Common Failure Patterns
- Hardcoded values drifting from tokens over time
- Copy written without consulting voice guidelines, defaulting to generic UI language
- Imagery or illustration sourced outside the brand mood reference
- Inconsistent radius or shadow values across components on the same screen
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.