Oracle

To provide code context for better debugging, you can use contextual prompting to bundle your prompt with relevant source files and error logs into a single request, enabling the AI to deliver targeted solutions based on your actual codebase.

Contextual prompting for codebase analysis is the process of packaging user prompts with specified project files to reduce AI guesswork. You need it when debugging complex issues, refactoring, or implementing features that require deep understanding of project structure and dependencies.

Yes, you need the oracle command-line tool installed and configured. This Skill relies on the oracle CLI to package your prompts with codebase files and supports both API and browser-based execution engines to interact with large language models like GPT-5.2 Pro.

Yes, you can use browser-based execution engines for AI code analysis. The Skill supports both API and browser-based execution engines to interact with large language models, allowing you to send detailed code context for tasks like debugging and refactoring.

The best way to package source files and error logs for AI refactoring is to bundle the selected codebase files with your problem description into a single request. This provides the AI with necessary project structure and dependency context to generate accurate solutions.

AI assistants give generic answers when they lack relevant code context. By packaging your prompts with specified codebase files, you provide the AI with necessary project structure and snippet context, reducing guesswork and improving the accuracy of feature implementation and debugging responses.