ice-score

Compute ICE scores from Impact, Confidence, and Ease inputs.

Updated Apr 7, 2026
One-click install
npx skills add https://github.com/haabe/tic-tac-toe --skill ice-score-haabe
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ice-score
Source: https://github.com/haabe/tic-tac-toe/tree/main/.claude/skills/ice-score
Command: npx skills add https://github.com/haabe/tic-tac-toe --skill ice-score-haabe

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

ICE scoring helps teams prioritize opportunities and features by quantifying impact, confidence, and ease, reducing guesswork and bias.

Core Features & Use Cases

  • Quantified prioritization: Score items on Impact, Confidence, and Ease to compute a consolidated ICE score.
  • Evidence-backed decisions: Include brief rationale and data points to support each score.
  • Ranking and bias checks: Sort by ICE score and apply bias checks to mitigate common heuristics.

Quick Start

Enter your items, score each on Impact, Confidence, and Ease, then compute and review the ICE scores.

Frequently Asked Questions about ice-score

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How does ICE scoring work for product feature prioritization?

ICE scoring ranks opportunities by multiplying Impact, Confidence, and Ease scores to produce a single prioritization metric. This method quantifies proposed features to reduce bias in decision-making.

How do I calculate ICE scores for proposed product ideas?

Calculate ICE scores by entering proposed items, assigning values for Impact, Confidence, and Ease, then computing the product of these three metrics. Include brief rationale to support each score.

Can I use ICE scoring for experiments across different teams?

Yes, ICE scoring applies to product ideas, features, and experiments across teams. The framework standardizes ranking to help teams decide what to work on next regardless of their specific domain.

What's the difference between ICE scoring and other prioritization methods?

ICE scoring distinguishes itself from other methods by requiring evidence-backed rationale for each score and applying bias checks to mitigate common heuristics. It standardizes ranking through the Impact, Confidence, and Ease formula.

How do I reduce bias when prioritizing product features?

Reduce bias in feature prioritization by applying bias checks to mitigate common heuristics. The ICE scoring framework supports this by requiring evidence-backed data points and brief rationale to justify each assigned score.