feature-prioritization-assistant

pmprompt/claude-plugin-product-management · updated Apr 8, 2026

$npx skills add https://github.com/pmprompt/claude-plugin-product-management --skill feature-prioritization-assistant
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summary

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.

skill.md

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...

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.426 reviews
  • Xiao Khanna· Dec 24, 2024

    Solid pick for teams standardizing on skills: feature-prioritization-assistant is focused, and the summary matches what you get after install.

  • Dhruvi Jain· Dec 12, 2024

    Registry listing for feature-prioritization-assistant matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Yuki Haddad· Dec 12, 2024

    I recommend feature-prioritization-assistant for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Yuki Yang· Nov 27, 2024

    Useful defaults in feature-prioritization-assistant — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Kiara Sanchez· Nov 15, 2024

    Registry listing for feature-prioritization-assistant matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Oshnikdeep· Nov 3, 2024

    Solid pick for teams standardizing on skills: feature-prioritization-assistant is focused, and the summary matches what you get after install.

  • Ganesh Mohane· Oct 22, 2024

    I recommend feature-prioritization-assistant for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Sakura Malhotra· Oct 18, 2024

    Registry listing for feature-prioritization-assistant matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Pratham Ware· Oct 6, 2024

    feature-prioritization-assistant has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Henry Rao· Oct 6, 2024

    Useful defaults in feature-prioritization-assistant — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

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