PlaybookPrompts

Write a style guide spec for a custom illustration system

Creative & Design illustrationart-directionvisual-identity

When briefing illustrators or generating consistent AI art, a written style spec is more reliable than a mood board alone. This prompt produces a language-based style guide that any illustrator or image model can follow.

Prompt
You are an art director. Write a written style guide for a custom illustration system for {{BRAND_NAME}}, a {{BRAND_DESCRIPTION}}.

Reference aesthetic (optional): {{REFERENCE_AESTHETIC}} (e.g., 'Penguin Books covers from the 1960s' or 'leave blank if none')

1. Line quality: Describe stroke weight, consistency, and edge treatment (e.g., 'uniform 2pt strokes, no tapering, hard edges only').
2. Color system: Define a palette of 4-6 colors with their role (primary, accent, neutral, background). Name them descriptively, not just by hex (e.g., 'dust clay' not '#C4A882').
3. Form language: Describe how shapes should feel—geometric vs. organic, simplified vs. detailed, flat vs. dimensional.
4. Subject matter: List 5 subjects or scenes that fit this style and 3 that must never appear.
5. Texture and finish: Describe any texture, grain, or paper-feel. If the style is clean/digital, say so explicitly.
6. One negative example: Describe in detail an illustration that would look wrong for this brand—be specific enough that an illustrator would immediately understand the boundary.

This prompt works best when the brand already has 2+ visual touchpoints. If starting from zero, complete a visual language spec first.
Variables to fill in
  • {{BRAND_NAME}}
  • {{BRAND_DESCRIPTION}}
  • {{REFERENCE_AESTHETIC}}

How to use this prompt

  1. Copy the prompt above (Copy button on the top-right).
  2. Replace each {{VAR}} with your own value. Variables: {{BRAND_NAME}}{{BRAND_DESCRIPTION}}{{REFERENCE_AESTHETIC}}.
  3. Paste it into one of the recommended tools below.
  4. Iterate: tighten constraints in the prompt if the output is generic.

Why this prompt is structured this way

The prompt is split into explicit steps because LLMs do better when the path is named, not implied. Each variable forces specificity at the input layer — vague inputs get vague outputs.

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