From pm-product-discovery
Prioritizes feature backlogs by scoring impact, effort, risk, and strategic alignment using ICE/RICE and Opportunity Score to recommend top 5. Use for scope decisions and ranking product ideas.
How this skill is triggered — by the user, by Claude, or both
Slash command
/pm-product-discovery:prioritize-featuresThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Evaluate and rank a backlog of feature ideas to identify the top 5 to pursue.
Evaluate and rank a backlog of feature ideas to identify the top 5 to pursue.
You are helping prioritize features for $ARGUMENTS.
If the user provides files (spreadsheets, backlogs, opportunity assessments), read and analyze them directly.
For framework selection guidance, see the prioritization-frameworks skill. Key recommendations:
Opportunity Score (Dan Olsen, The Lean Product Playbook) is recommended for evaluating customer problems: Opportunity Score = Importance × (1 − Satisfaction), normalized to 0–1. High Importance + low Satisfaction = best opportunities. Prioritize problems (opportunities), not solutions.
ICE is recommended for quick scoring of initiatives: Impact (Opportunity Score × # Customers) × Confidence × Ease. RICE adds Reach as a separate factor for larger teams.
The user will describe their product objective, desired outcomes, and provide feature ideas. Work through these steps:
Understand priorities: Confirm the product objective and success metrics.
Evaluate each feature against:
Recommend the top 5 features with:
Present as a prioritization table if helpful.
Think step by step. Save as markdown if the output is substantial.
npx claudepluginhub phuryn/pm-skills --plugin pm-product-discoveryPrioritizes feature idea backlogs by impact, effort, risk, and strategic fit; recommends top 5 with rationale and trade-offs. Use for backlog ranking, scope adjustment, product idea scoring.
Applies RICE, MoSCoW, Kano, ICE, and Opportunity Scoring frameworks to rank features and backlog items by priority.
Scores and prioritizes feature lists or initiatives using RICE, ICE, or custom frameworks. Outputs ranked tables with scores, rationales, cut lines, and capacity recommendations.