How does this skill help with roadmap planning?

It provides structured models like Value vs. Effort and the Kano Model to help you visualize strategic priorities and sequence features effectively.

Which prioritization framework should I use?

It depends on your context: use ICE for speed and experiments, RICE for data-driven rigor with large backlogs, and MoSCoW for defining MVP scope.

Can I use this for non-software projects?

Yes, while designed for product management, frameworks like Weighted Scoring and Value vs. Effort are effective for any complex decision-making process.

Does this skill provide reusable templates?

Yes, the skill includes standardized Markdown templates for all seven frameworks to ensure consistent documentation across your development team.

What is the RICE scoring formula?

RICE stands for Reach, Impact, Confidence, and Effort. The final score is calculated as (Reach × Impact × Confidence) / Effort.

AI Product Prioritization Methods

Name: AI Product Prioritization Methods
Author: slgoodrich

byslgoodrich

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コラボレーションツール

Applies industry-standard frameworks like RICE, ICE, and MoSCoW to prioritize product features and roadmap decisions.

概要

This skill empowers product teams and developers to make data-driven decisions by implementing seven core prioritization frameworks directly within Claude Code. It provides specialized guidance for ranking backlogs, scoping MVPs, and managing resource allocation using methods such as RICE, ICE, Kano, and Value vs. Effort. By leveraging structured templates and decision trees, users can move beyond gut feelings to create defendable, transparent product strategies that balance user value against technical constraints.

主な機能

Facilitates data-driven MVP scoping and backlog grooming
Provides ready-to-use Markdown templates for feature scoring and ranking
Includes a framework selection guide based on data availability and urgency
Supports strategic trade-off analysis for resource allocation
Implements 7 industry-standard prioritization frameworks (RICE, ICE, MoSCoW, etc.)
6 GitHub stars

ユースケース

Scoping a Minimum Viable Product (MVP) using the MoSCoW method
Ranking a large feature backlog with RICE scoring for a quarterly roadmap
Conducting quick growth experiment prioritization using the ICE framework

概要

主な機能

Facilitates data-driven MVP scoping and backlog grooming
Provides ready-to-use Markdown templates for feature scoring and ranking
Includes a framework selection guide based on data availability and urgency
Supports strategic trade-off analysis for resource allocation
Implements 7 industry-standard prioritization frameworks (RICE, ICE, MoSCoW, etc.)
6 GitHub stars

ユースケース

Scoping a Minimum Viable Product (MVP) using the MoSCoW method
Ranking a large feature backlog with RICE scoring for a quarterly roadmap
Conducting quick growth experiment prioritization using the ICE framework