/prioritize-assumptions
Prioritize assumptions using an Impact × Risk matrix and suggest experiments for each. Use when triaging a list of assumptions, deciding what to test first, or applying the assumption prioritization canvas.
Claude Code
$ npx -y skills add phuryn/pm-skills --skill prioritize-assumptions --agent claude-code
Codex
$ npx skills add phuryn/pm-skills --skill prioritize-assumptions -a codex -y
Cursor
$ npx skills add phuryn/pm-skills --skill prioritize-assumptions -a cursor -y
Gemini CLI
$ npx skills add phuryn/pm-skills --skill prioritize-assumptions -a gemini-cli -y
GitHub Copilot
$ npx skills add phuryn/pm-skills --skill prioritize-assumptions -a github-copilot -y
OpenCode
$ npx skills add phuryn/pm-skills --skill prioritize-assumptions -a opencode -y
Windsurf
$ npx skills add phuryn/pm-skills --skill prioritize-assumptions -a windsurf -y
SKILL.md
prioritize-assumptions.SKILL.mdname: prioritize-assumptions
description: "Prioritize assumptions using an Impact × Risk matrix and suggest experiments for each. Use when triaging a list of assumptions, deciding what to test first, or applying the assumption prioritization canvas."
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:
1. **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
2. **Categorize each assumption** using the Impact × Risk matrix:
- **Low Impact, Low Risk** → Defer testing until higher-priority assumptions are addressed
- **High Impact, Low Risk** → Proceed to implementation (low risk, high reward)
- **Low Impact, High Risk** → Reject the idea (not worth the investment)
- **High Impact, High Risk** → Design an experiment to test it
3. **For each assumption requiring testing**, suggest an experiment that:
- Maximizes validated learning with minimal effort
- Measures actual behavior, not opinions
- Has a clear success metric and threshold
4. **Present results** as a prioritized matrix or table.
Think step by step. Save as markdown if the output is substantial.
---
Further Reading
- [Assumption Prioritization Canvas: How to Identify And Test The Right Assumptions](https://www.productcompass.pm/p/assumption-prioritization-canvas)
- [Continuous Product Discovery Masterclass (CPDM)](https://www.productcompass.pm/p/cpdm) (video course)
Read more
name: prioritize-assumptions description: "Prioritize assumptions using an Impact × Risk matrix and suggest experiments for each. Use when triaging a list of assumptions, deciding what to test first, or applying the assumption prioritization canvas."
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:
1. **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
2. **Categorize each assumption** using the Impact × Risk matrix:
- **Low Impact, Low Risk** → Defer testing until higher-priority assumptions are addressed
- **High Impact, Low Risk** → Proceed to implementation (low risk, high reward)
- **Low Impact, High Risk** → Reject the idea (not worth the investment)
- **High Impact, High Risk** → Design an experiment to test it
3. **For each assumption requiring testing**, suggest an experiment that:
- Maximizes validated learning with minimal effort
- Measures actual behavior, not opinions
- Has a clear success metric and threshold
4. **Present results** as a prioritized matrix or table.
Think step by step. Save as markdown if the output is substantial.
---
Further Reading
- [Assumption Prioritization Canvas: How to Identify And Test The Right Assumptions](https://www.productcompass.pm/p/assumption-prioritization-canvas)
- [Continuous Product Discovery Masterclass (CPDM)](https://www.productcompass.pm/p/cpdm) (video course)
72 PM skills and 42 chained workflows across 9 plugins. Claude Code, Cowork, and more. From discovery to strategy, execution, launch, growth, and shipping AI-built code. Designed for Claude Code and Cowork. Skills compatible with other AI assistants.
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Questions about prioritize-assumptions.
- Which coding agents can use prioritize-assumptions?
- prioritize-assumptions installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.

