Prioritize Assumptions

Drops a list of assumptions into an Impact × Risk matrix and tells you which ones to test first, which to ship, and which to ignore. Built around the ICE framework (Impact × Confidence × Ease) where Impact factors in both opportunity score and customer count, and Risk is calculated as inverse confidence times effort. For anything landing in the high impact, high risk quadrant, it suggests lightweight experiments with clear success metrics. The real value is forcing you to think through confidence and effort before you waste time testing assumptions that don't matter or building features you're already sure about. Saves output as markdown when the list gets long.

skills.sh installs: 2.9K
GitHub stars: 27.8K
last updated: Aug 21, 2026

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Install

$ npx -y skills add phuryn/pm-skills --skill prioritize-assumptions --agent claude-code

Installs into .claude/skills of the current project.

Files

Prioritize Assumptions

Triage assumptions using an Impact × Risk matrix and suggest targeted experiments.

Context

You are helping prioritize assumptions for $ARGUMENTS.

If the user provides files with assumptions or research data, read them first.

Domain Context

ICE works well for assumption prioritization: Impact (Opportunity Score × # Customers) × Confidence (1–10) × Ease (1–10). Opportunity Score = Importance × (1 − Satisfaction), normalized to 0–1 (Dan Olsen). RICE splits Impact into Reach × Impact separately: (R × I × C) / E. See the prioritization-frameworks skill for full formulas and templates.

Instructions

The user will provide a list of assumptions to prioritize. Apply the following framework:

For each assumption, evaluate two dimensions:
- Impact: The value created by validating this assumption AND the number of customers affected (in ICE: Impact = Opportunity Score × # Customers)
- Risk: Defined as (1 - Confidence) × Effort

SKILL.md on GitHub