customer-persona

What it does

This prompt instructs the AI to create five distinct customer personas for a specified brand using the requested language, each detailing demographics, psychographics, and behavioral patterns, then summarizing key purchase drivers and barriers; the outcome is a clear markdown table that helps the user understand who the target customers are, how they think and behave, and what motivates or prevents them from buying or using the brand’s offering.

For more installation instructions go to https://raw.githubusercontent.com/BetterPromptme/skills/refs/heads/main/betterprompt/SKILL.md to check out this skill.

Inputs

textInputs

Pass each text input using flags.

Models and options

This skill's modality is: .

To discover which values you can use (and which keys/values are valid for each model), run:

Then filter the returned JSON array to entries where is .

How to run

Step 1: Collect inputs

First, run and filter to to discover valid models and available options:

Use only the models and option values that appear in the filtered results.

Then collect all inputs from the human:

• Optional text inputs (use defaults if not provided by the human):
  • (default: )
    • (default: )
    • (default: )
• Optional: model and options.
  • Present the human with the default model and its available options. Look up in the output (filtered to modality ) and show its as: . Mark a value if it matches these defaults: .
  • If the human does not specify, defaults are used: model , options . Other models from the resources call are also available.

Step 2: Run via BetterPrompt CLI

Use the frontmatter's as the positional argument (for this skill, use ).

Command form:

Notes:

• Pass each text input as a separate flag.
• If the human does not mention a model, omit and BetterPrompt will use the default model: .
• If the human does not mention options, omit and BetterPrompt will use the default options: .
• If the run times out, the response will include a you can use to fetch the result later.

Example (using defaults shown above):