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How to Build a Perfectly-Contextualized Prompt for Complex Code Analysis with Repo Prompt

Use Repo Prompt to gain surgical control over your AI's context. This workflow shows you how to manually select specific code files, combine them with a detailed prompt and a persona, and generate a highly-contextualized input for an LLM like Claude or Gemini.

From How I AI

How I AI: Ryan Carson's 3-Step Playbook for Structured AI Development in Cursor

with Claire Vo

How to Build a Perfectly-Contextualized Prompt for Complex Code Analysis with Repo Prompt

Tools Used

Claude

Anthropic AI assistant

Gemini

Google AI assistant

Step-by-Step Guide

1

Select Specific Files in Repo Prompt

Open your project in the Repo Prompt desktop application. Instead of providing the entire repository, carefully select only the files that are directly relevant to the task you need to perform, such as specific components or schema files.

2

Compose Your Query and Add a Persona

In the Repo Prompt user interface, write your specific question or instruction. Enhance the prompt by adding one of the built-in 'stored prompts,' such as an 'Architect' persona, to give the AI additional instructions on how to approach the problem.

Prompt:
how can I improve the maintainability of this code?
3

Generate and Copy the Full Context

Repo Prompt will then combine your selected file contents, your query, and the persona instructions into a single, perfectly formatted prompt. It uses XML tags like <file_contents> to structure the information clearly for the LLM.

4

Paste into Your Preferred LLM

Copy the entire generated prompt from Repo Prompt and paste it directly into a powerful LLM like Claude or Gemini. The precise and well-structured context will result in a much higher quality and more relevant answer.

Pro Tip: This method is ideal for complex tasks like architectural reviews or difficult refactors where incorrect or incomplete context could lead the AI astray.

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