arn-spark-feature-extract

To generate a feature backlog from use cases and prototypes, run the extraction command in your repository root to ingest artifacts and produce prioritized feature entries with traceable references.

You can map user journeys to features for backlog traceability by processing journey artifacts alongside use cases, which generates feature entries with explicit journey mappings and upstream document references.

To extract features for a prioritized product backlog, you need artifacts like product concepts, architecture visions, spike results, style briefs, static and clickable prototypes, use cases, and visual grounding assets.

Yes, you can use extracted feature entries to drive implementation order in an issue tracker, as the process prepares artifact references and generates a feature backlog index designed for downstream spec writing.

The best way to organize a feature backlog from multiple project artifacts is to consolidate product concepts, prototypes, and debates into lean feature entries with UC references and visual targets for a traceable path.

Clickable prototypes are not strictly required for extracting features into a backlog; the process ingests available artifacts including static prototypes, style briefs, and use cases to assemble prioritized feature entries.