Why it is written this way
Without a structured image prompt template, generating images on the fly will result in a visual feed that looks disjointed and inconsistent after a few months. Different team members describe things differently, and even the same creator rarely remembers the exact wording used previously. This prompt divides image descriptions into locked, consistent constants and flexible, swappable variables.
Dividing the task into three structured steps is essential. Asking the AI to simply "create a brand guide" usually results in generic adjectives and theoretical fluff. By forcing a pipeline of extracting traits → defining fixed vs. variable elements → locking into a syntax template, you can verify each step's logic before proceeding, preventing errors from cascading.
Specifying the exact format for each phase ensures high utility. Receiving Step 2 as a table answers "why is this locked?", and getting 2 concrete examples in Step 3 immediately tests whether the template works in practice. This bridges the gap between abstract brand theory and an actionable prompt framework.
The final review step forces the model to self-audit the Step 3 template against the Step 2 decisions. When tasks are partitioned, models sometimes omit elements; requiring self-verification catches these gaps. The concluding one-line adjustment note is included because brand guidelines naturally evolve over time rather than remaining static.
Unfamiliar terms? See Aha AI: prompt, output-format
Compared with a bad example
Create a brand image guide for our cafe. I want to unify the photo tone for our Instagram.
This prompt yields vague, abstract statements like "warm, cozy aesthetic" and "consistent tone and manner." While it sounds reasonable on paper, it provides no actual prompts for image generation AI tools, forcing creators to reinvent the wheel from scratch every time.
Variations
Auditing adherence to existing brand rules
I want to verify whether our recent visuals adhere to our established brand image rules. The brand is: {{brand name}}. Below are descriptions of recently published images. Break down deviations across style, color, lighting, and composition, and present a table showing how many images violated each criterion. Then, provide a one-line recommendation for each element indicating whether we should refine the rulebook or adjust the image generation process. """ {{existing image descriptions}} """
Maintaining rules is just as critical as making them. Counting specific deviations helps distinguish whether the guideline needs updating or the creator's prompting habits need correcting.
Expanding to a new marketing channel
We want to adapt our existing image rules to a new channel. Our brand is: {{brand name}}, and our full list of active channels (including the new one) is: {{target channels}}. Keep our fixed prompt phrases unchanged, and provide a table detailing the swappable slots needed for channel-specific requirements such as aspect ratio, negative space, and text overlay placement. If any fixed phrase conflicts with the new channel's format, identify the issue and propose an alternative.
Writing an entirely new rulebook every time a channel is added creates fragmented guidelines. This variant keeps the core aesthetic locked while expanding only the variable slots.
Model notes
Save the final template in your team's documentation for shared use. The core prompt structure remains usable even if you switch image generation tools; simply adapt the aspect ratios and tool-specific parameters accordingly.
The square brackets [...] in the template are placeholders meant to be filled in by humans, not native syntax recognized by image generators. Remove the brackets and replace them with actual descriptive terms before generating. Settings like aspect ratio (--ar) should ideally be set in tool parameters rather than left within the main visual prompt.
Related prompts
Last updated 2026-09-02 · Found a mistake? Let us know