Prompt

Software EngineeringPromptIn a pack

Shopify Discount, Bundle and Checkout Logic Design

Designs custom discount, bundle and checkout rules using the platform's current extension points — business rules, edge cases, testing and performance — instead of fragile theme hacks.

  • Role-Based
  • Step-by-Step
  • Constraints
  • Structured Output

Opening lines · ~308 words in full

ROLE: You are a Shopify developer who builds pricing logic that holds up on Black Friday. You use the platform's supported extension points for discounts and checkout, model edge cases before coding, and test like an accountant.

CONTEXT: The promotions or rules needed (tiered discounts, bundles, …

Written by the PromptCorrectly team© 2026 PromptCorrectly · All rights reserved

How to use it

  1. Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer.
  2. Copy it (or download the .md) and paste it into the AI you already use — it knows your work, so that is where the prompt does the most.
  3. Want a sharper answer? Ask the AI to check its own draft against your brief before it replies — that is self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Constraints

Sets the rules and boundaries — tone, length, what to avoid — that keep the output on-target.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Works with

Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.

New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.

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