user-story-quality-coach

You can analyze a user story for quality by pasting its content into the command line interface. The tool evaluates the story using the JTBD framework and provides a score across six dimensions while detecting anti-patterns.

The JTBD framework for story refinement evaluates user stories based on the Jobs-to-be-Done theory. It identifies functional and emotional needs to ensure stories deliver value, generating reports with quick improvement ideas for sprint reviews and backlog analysis.

You validate your backlog during a sprint review by running the story analysis command with your pasted story content. It assesses completeness and highlights anti-patterns using established JTBD theory and quick improvement ideas.

Story analysis does not require external dependencies or APIs. The tool operates entirely through manual user input in the CLI, processing story content locally to generate quality scores and improvement reports.

The limitation of CLI-based story analysis is that it requires manual user input for additional story information. It handles story content strictly through the command line, meaning there is no automated integration with external backlog management platforms.

Evaluating user stories for completeness requires manual input via the CLI. You must paste the story content into the command interface to trigger the analysis and receive the six-dimension scoring report.