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Zhongwei Li
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---
name: prioritize-hypotheses
description: Scores experiment backlog using impact, confidence, effort, and guardrail readiness.
usage: /growth-experiments:prioritize-hypotheses --source backlog.csv --capacity 6 --framework rice
---
# Command: prioritize-hypotheses
## Inputs
- **source** backlog file, experiment tracker, or Notion database ID.
- **capacity** number of experiments that can run in the next sprint/cycle.
- **framework** ice | rice | custom; determines scoring weights.
- **guardrails** optional JSON/CSV for mandatory guardrail requirements.
- **filters** tags or OKRs to focus on (acquisition, activation, retention, monetization).
## Workflow
1. **Data Ingestion** load backlog, normalize fields, and enrich with latest metrics.
2. **Scoring Engine** calculate ICE/RICE/custom scores, factoring guardrail readiness.
3. **Portfolio Mix** ensure balance across funnel stages and surfaces; flag conflicts.
4. **Capacity Planning** fit highest-value tests into available slots, accounting for owners + effort.
5. **Decision Pack** generate prioritized list, rationale, and trade-off notes for approval.
## Outputs
- Ranked backlog with scores, dependencies, and guardrail status.
- Capacity plan showing selected tests plus waitlist.
- Decision memo summarizing trade-offs and next actions.
## Agent/Skill Invocations
- `experimentation-strategist` orchestrates prioritization + governance alignment.
- `insight-analyst` validates data quality and metric assumptions.
- `hypothesis-library` skill links past learnings to current ideas.
- `guardrail-scorecard` skill enforces readiness requirements.
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