feature-prioritization-assistant
Calculate RICE scores and prioritize features systematically. Use when building your product roadmap and need to make data-driven prioritization decisions.
What this skill does
## Domain Context This skill implements a proven product management framework. The approach combines best practices from industry leaders and is designed for practical application in day-to-day PM work. ## Input Requirements - Context about your product, feature, or problem - Relevant data, research, or constraints (recommended but optional) - Clear articulation of what you're trying to achieve # Feature Prioritization Assistant ## When to Use - Building your product roadmap - Need to choose between multiple feature ideas - Stakeholders are debating which features to build first - Want to make data-driven prioritization decisions - Need to justify prioritization decisions to leadership ## What This Skill Does Helps you systematically evaluate and prioritize features using the RICE framework (Reach, Impact, Confidence, Effort), providing scores and recommendations. ## Instructions Help me prioritize these features using the RICE framework. For each feature, help me estimate: 1. **Reach**: How many users will this impact per month? 2. **Impact**: How much will this impact each user? (Scale: 0.25=minimal, 0.5=low, 1=medium, 2=high, 3=massive) 3. **Confidence**: How confident are we in our estimates? (Scale: 0-100%) 4. **Effort**: How many person-months will this take to build? Then calculate the RICE score: (Reach × Impact × Confidence) / Effort Features to evaluate: [List your features with any context you have] ## Best Practices - Gather data on current user behavior before estimating Reach - Base Impact on user research and pain point severity - Be honest about Confidence levels - lower confidence for assumptions - Include design, development, and testing time in Effort estimates - Revisit estimates after initial discovery work - Consider dependencies between features ## Example **Input:** 5 features (notifications, dark mode, API access, mobile app, analytics dashboard) **Output:** RICE scores calculated for each, ranked list with reasoning, recommendations on which to prioritize, and suggestions for validating assumptions on low-c...
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