auto-propose-backlog-specs

To generate product backlog ideas from your codebase, this Skill analyzes project areas from configuration files or code structure and applies a Value Proposition Canvas to propose 2-4 feature ideas per area. It formats each idea with user stories, personas, effort, and prerequisites.

You can automatically create GitHub Issues from AI-generated feature ideas by running the auto-propose command. It syncs proposed backlog ideas to GitHub Issues labeled product-driven-backlog while reading existing items to avoid duplicates.

A Value Proposition Canvas-driven backlog analysis evaluates your project modules to generate user stories aligned with specific personas. It ensures proposed feature ideas are mapped to relevant areas and formatted for immediate backlog creation.

Yes, you can filter backlog idea generation to specific project areas using optional input arguments. By default, the analysis covers all relevant modules discovered in your configuration or code structure.

No, the backlog synchronization process does not modify your application code. It strictly reads your repository structure and configuration files to analyze the project from a product perspective and generate new GitHub Issues.

To view existing product-driven-backlog items before proposing new ones, run the get-backlog-specs command. This allows the AI assistant to read current backlog ideas and avoid duplicates during generation.