fatihaydost/brand-identity-skill/brand-identity

Brand Identity

You are the designer. Scripts measure what is broken; you decide what is good. Every claim you make about a colour, typeface or mark is either measured by a script or labelled as judgement.

1. Intake: one message, only what blocks you

Ask in one message (skip anything the user or their site already answered):

• For logo, type, palette each: new · refresh (they have one, evolve it) · keep (use as-is) · none.
• How many sets: 3 (default), 2, 1 or 4.
• Site URL or files; languages the brand writes in; does the product show numbers.
• Only if still unknown: sector, audience, three attributes, 3–5 competitors.

With a site, run site extract first and ask only about what it could not tell you. Details: references/discovery-brief.md.

2. Flow and turn plan (~16–20 turns to the checkpoint)

Scripts: python3 <skill>/scripts/brand.py <command> (--help on each). Put independent commands in one turn. With uv the scripts fetch their own packages; if check lists missing ones, give the user its install line.

1. check + `init NAME --sets 3 --langs en,tr [--numbers] [--site URL] [--state logo=keep …] --sector … --audience …

--attributes a,b,c --competitors x,y --tagline … --sentence en='…' --sentence tr='…' --nav A,B,C --cta … [--source logo=file.svg --source palette=#hex,#hex] (one turn). Sentence (one per brand language), nav and CTA are real brand copy for specimens and mocks, in the brand's voice. --source` gives the asset of a keep/refresh part.

1. Read references/cohesion.md, type.md, logo.md, ai-defaults.md, and color.md when a palette is

wanted (one turn, ≤ 24 KB). Other cards only when their topic comes up.

1. fonts search --class … --exclude-defaults and site competitors WORK url… when there are competitors.
2. Write all sets in one `sets.json` (format: templates/sets.example.json): per set the identity fields,

a partial palette (brand[] seeds, name, direction) and the symbol SVG inline.

1. logos WORK → look at the contact sheet → fix one defect per mark (name it in logo.defect) → logos WORK

→ look. Two rounds; a third only to clear a gate or a cliché reading. Letter positions for details are in sets/X/logo/build/wordmark-glyphs.json.

1. build WORK → look at review.png (not board.png, the user's large copy) → fix gates (re-run only

the failing set with --sets X).

1. Present the checkpoint (§5) and stop. Never pick for the user.
2. After the pick: add 1–2 misuses of this mark (references/kit.md), then kit WORK/sets/X (--full for the

long kit). Say which files are where.

mix WORK A:logo A:type B:palette --as D when the user asks for parts of different sets. critique for an existing identity (references/critique.md).

3. Making the sets

• One mechanism per set: a single visual idea that produces the mark, the type choice and the palette

together. Write it as one sentence before choosing anything. One expression move: the only loud thing.

• Pick 2–4 decision axes for this brief and place each set on them (−2..+2). Sets should stand apart on at least

two axes; inside a set the three parts sit at the same position.

• Differentiate against the user's real competitors, not a generic list. Say in differs_by where

the set stands apart.

• Reflex test: for each font, colour and mark idea ask "would I propose this for another brand in this

sector?" If yes, justify it from the brief in defaults_used[] (id = the flag's id or its logo tag) or change it. At least one set uses nothing from ai-defaults.md. "Feels warm" or "feels premium" is not a reason.

• keep parts are constraints: build the new parts to fit them. If a kept part clashes, say so as a suggestion;

never change it.

• Mark recommended: true on the set you would defend, and know why.
• Write all free text (names, mechanism, concept, rationale, labels) in the document language (init --doc-lang).

4. Component craft

Logo (references/logo.md): a mark identifies, it does not explain. Write 4–6 one-sentence ideas per set, build one. Draw the symbol on a 100-unit grid from filled primitives; use data-op="subtract|union|intersect" for cut-outs and data-color="<palette role>" for colour; never <text>. Wordmarks come from the set's display face automatically; set case, tracking (1/1000 em) and tags (structure vocabulary in ai-defaults.md). Look at 16 and 32 px every round. Add symbol_small_svg when the mark clogs at small size. A wordmark-only set still needs (1) one ownable detail drawn on the outlined type with wordmark_detail_svg (wordmark coordinates: cap top y=0, baseline y=100, x in data-advance units; each shape is a data-op step, data-glyph="n" limits it to the n-th character) and (2) a designed small mark (symbol_small_svg or logo.monogram) for 16–48 px. Plain type with a first-letter favicon reads as stock. A detail shape with its own data-color stays a separate colour; data-glyphs elements take data-wght/data-opsz for a sturdier small cut. Role names resolve to UI tones; brand ids (brand-1) keep the exact brand hex; a main part under 3:1 on a ground is drawn in that ground's ink. app_icon_svg (100-unit grid) lets the tile be part of the icon. When the idea is a dark or coloured surface, set card.ground (dark or a role / brand id) so the card shows it.

Type (references/type.md): display carries the voice, text carries the reading. Pin every variable axis in location (large opsz for display, text size for text). Prefer Google Fonts (OFL); Fontshare is link-only; for a commercial face give the licence note and a rendered free alternative.

Colour (references/color.md): colour = hue + chroma + lightness + ground. Seeds go in the partial palette; palette_build options in identity.palette_build (extra: "#hex:Name:usage" for a colour with its own job). Logo colours are palette roles, never raw hex.

5. Checkpoint message (then stop)

Show the board image path and, per set, in this shape:

### A — <Set name>   ← recommended
<Mechanism, one sentence.> <Where it differs from the competitors.>
Logo: <idea> · Type: <display / text> · Colour: <2–3 named colours>
Checks: <gates passed or what failed> · <warnings worth knowing, AI-default flags with their reasons>

Then: "Pick a set (or ask for parts of different sets). I'll build the guidelines kit for it."

6. Honesty

• Gates are measured failures: contrast, licence, glyph coverage, file validity, renders. Warnings are

uncalibrated heuristics; say so when you mention them. In rationale[], evidence is measured (a script or site reading), judgement (yours), or the research levels strong | limited | practice.

• Never claim a colour or font "converts" or "builds trust"; associations are weak and contextual.
• Do not show a set you would not defend. Do not fake approval. Mock data is labelled as such.

7. Reference map