brand-identity
Brand identity sets from one brief - logo, typography and colour palette built together, measured (contrast, colour blindness, glyph coverage, font licences, small-size logo renders) and compared side by side as identity cards, shown on the user's own site, then a brand guidelines kit (PDF, logo files, tokens) for the chosen set. Use for a new brand or any part of one (logo, fonts, colours, or a mix), for refreshing an identity, or for critiquing one, even if the user only says "branding".
Install
npx skills add https://github.com/fatihaydost/brand-identity-skill --skill brand-identityCritique
Critique mode: "what do you think of our identity / logo / fonts / colours". Output = gates, short findings per
component, the three measurable fixes that matter most. No overall score: the evidence supports no weighting.
Critique the work, never the person; name what works before what doesn't. Tags: [strong] [limited] [practice].
Flow
- Context: sector, competitors, position, markets, languages. Read the site first; ask ≤ 3 questions; write guesses under "Assumptions".
- Collect:
brand.py critique --site URLand/or--logo f.svg --fonts … --palette p.json --langs …. Values read from a site are approximate and labelledmeasured; confirm colour roles with the user before judging (site-preview.md). - First impression (two seconds): what would a stranger say this brand is, what do you remember?
- Gates, then findings per component, then top three.
Gates (measurable or irreversible)
Unchecked gates are marked "not checked: reason", never passed.
Findings (two to four lines per component; evidence for each)
- Logo: distinctive vs the competitor shelf; does it identify without explaining; one colour, reversed, 16 px;
construction (near-equal radii, clogged joins, false holes); category clichés from
ai-defaults.md§B. - Type: role split (voice vs reading); class against the competitor type map; weights,
tnum, I/l/1; default-list hits; licence cost. - Palette: category legibility vs differentiation, ownability, system (roles, scales, drift: many near duplicates), producibility (dark ground, print), fit of lightness and chroma to the personality.
- Cohesion: one mechanism or three unrelated picks? Do the components sit at the same axis positions? Is
there one loud thing or several?
"Feels modern" is not evidence; "primary L 0.62, C 0.19, saturated mid-light, reads energetic
(Labrecque & Milne 2012,
[limited])" is.
Top three
Order: failed gates (unreadable first, then confusion, licence, glyphs), then the biggest weakness against the brief, cheapest change first among equals (tokens before logo). Each fix states:
- What: "CTA fill #4FA3E0 → #1F6FB2 (primary-700)".
- Measured effect: "white label 2.6:1 → 5.1:1".
- Why: one sentence tied to the brief or a finding.
- Cost: tokens · site CSS · reprint · logo redraw. Never "improve contrast". Re-run the audit after a fix; quote before/after. A clean audit means nothing is measurably broken, not that the identity is good.
Template (plain words; numbers go to the audit file)
Refresh = Create with that component in refresh state.