Docs & technical writing
AuraScore 81/100

Multimodal Visual Style Token Specification

Specify design system visual style tokens and compositional weights for generative image models.

Use this template when building a visual design token specification that standardizes style matrices, lighting parameters, and camera compositions across generative prompt pipelines.

Template

Role: Lead Multimodal Design Technologist and Documentation Architect

Context

  • Design System Name: {{style_system_name}}
  • Aesthetic Target: {{target_aesthetic}}
  • Base Text/Image Encoders: {{base_clip_encoders}}
  • Compositional Tokens: {{composition_tokens}}
  • Lighting Attributes: {{lighting_attributes}}
  • Camera & Lens Primitives: {{camera_primitives}}

Task

Author a comprehensive Visual Style Token Specification for {{style_system_name}} that maps standardized brand design primitives into reproducible multimodal prompt components and weight coefficients.

Method

  1. Define the semantic token hierarchy and prefix nomenclature for {{style_system_name}}.
  2. Construct the core style definition mapping {{target_aesthetic}} to specific prompt descriptor clusters.
  3. Specify prompt token syntax and numerical weights compatible with {{base_clip_encoders}}.
  4. Standardize spatial and framing parameters using the tokens defined in {{composition_tokens}}.
  5. Standardize environmental and illumination variables using {{lighting_attributes}}.
  6. Formulate optical lens, aperture, and sensor keywords defined in {{camera_primitives}}.
  7. Provide an integration matrix mapping token combinations to negative prompt dampeners.

Constraints

  • MUST express all token weights as exact decimal coefficients (e.g., token:1.15).
  • MUST define positive and negative prompt token pairs for every aesthetic attribute.
  • MUST NOT use subjective qualitative descriptions without actionable prompt keywords.
  • Ensure exact terminology alignment with photographic and cinematographic standards.

Output format

  1. Design System Scope (System: {{style_system_name}}, Target: {{target_aesthetic}})
  2. Token Classification Registry (Categorized tables with Token Name, Prompt Keyword, Default Weight)
  3. Compositional & Camera Matrices (Covering {{composition_tokens}} and {{camera_primitives}})
  4. Environmental Lighting Rules (Covering {{lighting_attributes}})
  5. Canonical Assembly Template (Structural formula for token string concatenation)

Self-review

  • Confirm every token in {{composition_tokens}} and {{lighting_attributes}} has a concrete weight assignment.
  • Verify compatibility of token weights with {{base_clip_encoders}}.
  • Ensure no overlapping or contradictory style keywords are assigned default priority.
AuraScore breakdown
81/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering10/12 · Adequate

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency7/10 · Adequate

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

writing-content
writing-docs
image-multimodal-prompting
design-tokens
visual-spec
multimodal