Debugging AI Prompts for Engineering Teams
Efficiently identify issues, test solutions, and ensure code stability for product updates and releases by leveraging these AI prompts.
Compile bug fixes
Compile bug fixes related to [Feature] in [Version] of the [Project] code repository. Focus on identifying changes made between [Start Date] and [End Date], and categorize the fixes by severity
Locate error handling examples
Locate examples of error handling in [Programming Language] in the [Project] repository. Provide details on how errors are logged or managed, including any related documentation or comments in the code
Find bug resolution messages
Find Slack messages discussing the resolution of [Bug ID]. Prioritize messages related to debugging steps, fixes implemented, and any blockers encountered during resolution
Generate unit tests
Generate unit tests in [Testing Framework] for the [Function] in the [Project] repository. Ensure the tests cover edge cases, boundary conditions, and potential failure scenarios. Include mock data for dependencies and integrate with the project's existing test suite
Summarize code review feedback
Summarize code review feedback on [Developer]’s submissions in the [Repository] during [Date Range]. Organize feedback into categories such as suggestions, approval, and issues raised
Related Engineering prompt categories
