agent-prompt

You can automate AI agent prompts for codebase analysis by using a Skill that reads prompt files from a directory, applies them to your code context, and presents structured results for code reviews or documentation gaps.

Running a code review using AI prompts involves selecting a specific prompt like 'code_smells' from your prompts directory, which the system then dynamically executes against your codebase to identify potential issues and report them.

Yes, you can use dynamic prompting to find documentation gaps by applying targeted AI prompts to your current codebase context, which analyzes the code and generates summaries of missing or incomplete documentation.

Yes, you need prompt files stored in a 'prompts/' directory and scripting capabilities, as the system reads and selects prompts from this location to execute contextual AI tasks against your codebase.

With automated AI prompt execution, you can perform code analysis tasks such as identifying code smells, generating activity summaries, and detecting documentation gaps, all through dynamic prompt selection and contextual application.

AI agent prompting requires manual input to specify the prompt name, but the system automatically fetches the corresponding prompt file, applies it to the codebase context, and presents the analysis results.