devlyn:recommend-features

Feature spec prioritization analyzes your product spec, existing spec files, and codebase to score and rank candidates by dependency, value, readiness, complexity, and urgency, producing a top-5 build order shortlist.

To decide which feature specifications to build next, scan your docs/feature-specs directory and codebase to detect implementation signals, then rank specs by dependency clarity and user value to generate a prioritized MVP delivery list.

Yes, you can filter feature spec recommendations by specific areas like core, backend, frontend, api, cli, sdk, or auth, allowing you to narrow the prioritized build order to targeted product phases or entities.

The best way to generate a ranked shortlist for MVP delivery is to scan the repository codebase via grep for existing implementations, then score candidates by dependency, value, readiness, complexity, and urgency.

Yes, you need a docs/product-spec.md file and a docs/feature-specs directory, because the recommendation engine reads these files to understand mission-driven product planning workflows and detect current spec statuses.

Dependency analysis matters for product planning because it scores candidates using dependency clarity, ensuring that foundational behaviors, views, commands, tools, functions, integrations, and contracts are built in the correct order.