name: optimization.experiment_brief phase: optimization roles:
- Product Designer
- Product Manager
description: Prepare an experiment brief outlining hypothesis, design, success metrics, and operational plan.
variables:
required:
- name: hypothesis description: Hypothesis statement to validate.
- name: primary_metric description: Primary metric measuring experiment success. optional:
- name: secondary_metrics description: Supporting or guardrail metrics.
- name: audience description: User segment or cohort being targeted. outputs:
- Experiment overview with hypothesis, rationale, and metrics.
- Test design including variants, sample size, and timeline.
- Operational checklist for launch, monitoring, and decision-making.
Purpose
Ensure experiments are well-defined, measurable, and aligned with user experience considerations before launch.
Pre-run Checklist
- ✅ Align with analytics on measurement feasibility and sample size.
- ✅ Confirm design assets and engineering bandwidth for variants.
- ✅ Review related research or previous experiments for context.
Invocation Guidance
codex run --skill optimization.experiment_brief \
--vars "hypothesis={{hypothesis}}" \
"primary_metric={{primary_metric}}" \
"secondary_metrics={{secondary_metrics}}" \
"audience={{audience}}"
Recommended Input Attachments
- Design mockups or copy variations.
- Experiment backlog or learning agenda.
- Prior experiment analyses.
Claude Workflow Outline
- Summarize hypothesis, audience, and metrics.
- Detail the experiment design: variants, allocation, instrumentation, and run duration.
- Provide sample size estimation guidance and data dependencies.
- Outline monitoring plan, success criteria, and decision framework.
- Document collaboration and approval workflow.
Output Template
## Experiment Overview
- Hypothesis:
- Audience:
- Primary Metric:
- Secondary Metrics:
## Test Design
| Variant | Description | % Allocation | Key Changes |
| --- | --- | --- | --- |
- Expected Duration:
- Sample Size Estimate:
## Measurement & Monitoring
- Instrumentation Checklist:
- Data Quality Checks:
- Decision Cadence:
## Launch Plan
- Approvals:
- Launch Date:
- Responsibilities:
Follow-up Actions
- Secure approvals from product, design, engineering, and analytics leads.
- Schedule mid-test reviews to monitor guardrails.
- Plan post-test readout session.