What problem does it solve? Product managers struggle to objectively rank feature backlogs and synthesize qualitative customer research into actionable decisions. This Skill automates RICE scoring, portfolio analysis, roadmap generation, and interview insight extraction so prioritization and discovery work is grounded in data rather than gut feel. ## Core Features & Use Cases - RICE Prioritization: Score features by Reach, Impact, Confidence, and Effort from a CSV, with portfolio balance analysis (quick wins vs big bets) and capacity-based quarterly roadmap generation. - Customer Interview Analysis: Parse interview transcripts to extract pain points with severity, feature requests with priority, jobs-to-be-done, sentiment, themes, metrics, and competitor mentions. - PRD Templates: Four ready-to-use formats (Standard PRD, One-Page PRD, Agile Epic, Feature Brief) for documenting requirements at different stages. - Use Case: You have 20 feature requests from sales and customers. Export them to a CSV with reach/impact/confidence/effort values, run the RICE prioritizer with your team's quarterly capacity, and get a ranked roadmap showing which quick wins to ship first. ## Quick Start Ask the AI to prioritize your feature backlog by running the RICE prioritizer script on a CSV of features with your team's quarterly capacity in person-months.
