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Use define-hypothesis to define a testable hypothesis for [proposed change] affecting [target users], including success and guardrail metrics, validation approach, risks, and assumptions.
Required inputs
[proposed change]
[target users]
User-approved starter prompt based on a pinned source version; check current skill requirements before running. Task evidence ↗
SKILL.md
name: define-hypothesisdescription: Defines a testable hypothesis with clear success metrics and a validation approach. Use when forming assumptions to test or aligning a team on what success looks like, before any experiment is designed. To design the A/B test or experiment that will validate the hypothesis, use measure-experiment-design.license: Apache-2.0metadata: phase: define version: "2.1.0" updated: 2026-06-10 category: ideation frameworks: [triple-diamond, lean-startup, design-thinking] author: product-on-purpose
Hypothesis
A hypothesis is a testable prediction about how a change will affect user behavior or business outcomes. It transforms assumptions into explicit statements that can be validated or invalidated through experimentation. Well-formed hypotheses prevent teams from building features based on untested beliefs and create shared understanding of what success looks like.
When to Use
After problem framing, before committing to a solution
When designing experiments or A/B tests
When team members have differing assumptions about user behavior
Before investing significant engineering resources in a feature
When pivoting direction and need to validate the new approach
When NOT to Use
You are ready to design the actual A/B test (variants, sample size, duration) -> use measure-experiment-design; this skill frames what to test, not how
The problem itself is still unframed -> use define-problem-statement first
You want to organize many assumptions and ideas into a discovery structure -> use define-opportunity-tree
The team needs the full business-model picture, not one testable claim -> use foundation-lean-canvas
Instructions
When asked to create a hypothesis, follow these steps:
State the Belief
Articulate what you believe will happen. Use the structured format: "We believe that [action/change] for [target user] will [expected outcome]." Be specific about the intervention - vague hypotheses can't be tested.
Identify the Target User
Define who this hypothesis applies to. A hypothesis about "users" is too broad. Specify the segment: new users in their first week, power users with 10+ sessions, churned users returning, etc.
Define the Expected Outcome
What behavior change or result do you expect? Frame it in terms of user actions (complete onboarding, make a purchase, return within 7 days) rather than internal metrics when possible.
Set Success Metrics
Choose a primary metric that directly measures the expected outcome. Include secondary metrics that provide context and guardrail metrics that ensure you're not causing harm elsewhere.
Describe Validation Approach
How will you test this hypothesis? A/B test, user interviews, prototype testing, cohort analysis? Be specific about sample size, duration, and statistical requirements.
Document Risks and Assumptions
What could invalidate this hypothesis beyond the test results? What are you assuming to be true that you haven't validated?
Output Format
Use the template in references/TEMPLATE.md to structure the output. A complete hypothesis document fills every template section: Hypothesis Statement; Background & Rationale; Target User Segment; Success Metrics; Validation Approach; Risks & Assumptions; and Timeline.
Quality Checklist
Before finalizing, verify:
Hypothesis is falsifiable (possible to prove wrong)
Success metric has a specific numeric target
Target user segment is clearly defined
Validation approach is practical and time-bound
Pass/fail criteria are unambiguous
Hypothesis doesn't assume the solution works
Examples
See references/EXAMPLE.md for a completed example.