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From pm-skills
Runs RICE, ICE, MoSCoW, Weighted Scoring, and Kano frameworks against a list of features or initiatives. Produces a comparison table and executive summary with recommendation.
npx claudepluginhub product-on-purpose/pm-skills --plugin pm-skillsHow this skill is triggered — by the user, by Claude, or both
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/pm-skills:define-prioritization-frameworkThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 -->
Apply RICE, ICE, MoSCoW, Kano, and Value vs Effort frameworks for prioritizing features, roadmaps, backlogs, and trade-offs.
Applies RICE, MoSCoW, Kano, ICE, and Opportunity Scoring frameworks to rank features and backlog items. Produces scored tables, build order, and deprioritised items.
Scores and ranks product backlogs using RICE, WSJF, ICE, MoSCoW frameworks. Use for prioritizing features, roadmap decisions, and evaluating trade-offs.
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You run all applicable prioritization frameworks against a candidate list of work items. Your job is to (a) filter frameworks by data availability and context, (b) score each item explicitly per applicable framework, (c) produce a comparison table showing where rankings agree and diverge, (d) synthesize an executive summary with recommendation, and (e) flag what could go wrong with the prioritization.
Multi-framework analysis surfaces what single-framework selection hides. Where RICE and ICE agree, confidence rises. Where they disagree, the divergence reveals hidden assumptions worth examining - often the most valuable finding.
Filter frameworks by applicability: RICE requires quantitative reach/impact/effort inputs; ICE works with coarse estimates; MoSCoW is for binary commitment decisions; Weighted Scoring requires multi-criteria weights; Kano requires customer-research input (gated). Run all frameworks that pass the applicability filter. Do NOT reduce to one framework when multiple are applicable.
Required:
Optional but improves quality:
Before running, evaluate each framework against the available inputs. Run all frameworks that pass:
| Framework | Runs when | Excluded when |
|---|---|---|
| RICE (Reach * Impact * Confidence / Effort) | Quantitative reach, impact, effort estimates are available or user accepts an estimation scaffold | Inputs unavailable and user declines estimation scaffold |
| ICE (Impact * Confidence * Ease) | Always applicable; coarse estimates are acceptable | Not excluded; ICE is the lowest-input framework |
| MoSCoW (Must / Should / Could / Won't) | Decision involves binary commitment per item or scope bounding | Not applicable for pure ranking decisions without scope constraint |
| Weighted Scoring (multi-criteria with weights) | Multiple stakeholders or criteria apply; user provides or accepts proposed default weights | Single criterion dominates; or criteria are purely personal preference |
| Kano (Must-Have / Performance / Delighter) | Customer-research input (survey or interview data) is provided | Gated: excluded if no customer research is provided; explain why and suggest what research would unlock it |
At least one framework will always run (ICE is always applicable). Show which frameworks ran and which were excluded, with brief rationale.
Which frameworks ran, which were excluded, and why. Note any frameworks excluded due to missing inputs and what would unlock them.
What you were given. If any input is missing or assumed, note: "Reach was not provided; assumption: large reach unless flagged."
Run each applicable framework and produce its scoring table.
For RICE:
| Item | Reach (users/qtr) | Impact (0.25-3) | Confidence (%) | Effort (eng-weeks) | RICE Score | Notes |
|---|---|---|---|---|---|---|
| Item A | 1000 | 2 | 80% | 3 | 533 | High confidence on reach |
For ICE:
| Item | Impact (1-10) | Confidence (1-10) | Ease (1-10) | ICE Score | Notes |
|---|
For MoSCoW:
| Item | Bucket | Rationale | Risk if dropped |
|---|---|---|---|
| Item A | Must | Critical for launch | Cannot ship without |
For Weighted Scoring:
| Item | Criterion 1 (weight) | Criterion 2 (weight) | ... | Total Weighted Score |
|---|
For Kano:
| Item | Category (Must / Performance / Delighter / Reverse / Indifferent) | Customer evidence | Implication |
|---|
For each scored framework: items sorted by score or grouped by bucket. For scored frameworks, highlight the top 5 and bottom 5 with the gap between them.
A comparison table showing ranking position per item across all frameworks that ran. Surface divergence explicitly.
| Item | RICE rank | ICE rank | MoSCoW bucket | Agreement |
|---|---|---|---|---|
| Item A | 1 | 1 | Must | Strong |
| Item B | 2 | 8 | Should | Divergent |
For each Divergent item: explain the driver. Divergence usually means one scoring dimension is carrying most of the weight (e.g., ICE ranks item B 8th because Ease is very low, but RICE ranks it 2nd because Reach is massive). This is the finding.
Synthesize the comparison into a 3-5 sentence recommendation: which items to prioritize, which to defer, and what the most important divergence means for the team's decision. Flag if the recommendation changes materially under different frameworks or assumptions.
What if Confidence is wrong? What if Effort is doubled? Show 2-3 cases where the rank order changes, focusing on the items near the cut line.
Top items to fund; bottom items to defer or drop; what additional data would change the recommendation. Recommend NEXT STEP, not just the ranking.
What are these frameworks NOT measuring? Where could the frameworks lead astray? Where do they systematically favor certain item types over others?
You refuse to produce a ranking without minimum input quality. Specifically:
Empty / single-item list. If user provides 0 or 1 candidate items: "Prioritization requires at least 3 items to be meaningful. With fewer, just decide directly."
No context. If user provides items without saying what decision they are making: "I need to know what decision this prioritization is supporting. Sprint scope? Quarter scope? Hypothesis triage? Different contexts affect which frameworks apply."
Missing numerical inputs for RICE. If user asks for RICE scores without providing input data: "I cannot produce defensible RICE scores without reach, impact, confidence, and effort estimates. Options: (a) provide rough numbers per item; (b) I can produce an estimation scaffold - a structured worksheet showing how to estimate reach, impact, confidence, and effort for each item; (c) run ICE instead, which works with coarse 1-10 judgment and does not require quantitative inputs. Which would you prefer?" (ICE itself is never refused for missing data - it is the always-applicable coarse fallback.)
Wrong-framework insistence. If user insists on RICE for an early-stage hypothesis triage: "RICE assumes measurable impact and effort, which you do not have at this stage. I can produce a RICE table but the scores will be guesses. ICE or MoSCoW would be more honest. Want to proceed with RICE anyway, or switch?"
Single-stakeholder weighted scoring. If user asks for Weighted Scoring with criteria that only one stakeholder cares about: "Weighted Scoring is for multi-stakeholder trade-offs. If only one stakeholder's criteria apply, RICE or ICE would be simpler. Want to proceed or switch?"
Kano without customer research. If user requests Kano but provides no customer-research input: "Kano categories are only defensible with customer research. Without it, you would be guessing whether a feature is a Must-Have or a Delighter, which defeats the purpose. I have excluded Kano from this run. The other applicable frameworks have run above. To unlock Kano, provide customer survey or interview data (skill: discover-interview-synthesis or measure-survey-analysis)."
Score = (Reach * Impact * Confidence) / Effort
Score = Impact * Confidence * Ease
All three on 1-10 scale. Coarse but fast. Use when you need to triage 30+ ideas quickly. Do not use for committing significant capital.
Strong commitment communication; weak relative ranking within buckets.
Multi-criteria with explicit weights per criterion.
Score = Sum over criteria (Weight_i * Score_i)
Use when stakeholders disagree on what matters. Make the disagreement explicit via the weights.
Default criteria if not user-provided: business value, customer value, effort, risk, strategic fit - all at equal weight (20% each). Equal weights is itself a choice. Flag this explicitly: "These starting weights are equal; adjust them to reflect what your org actually values." Never silently apply weights.
Categorize features by how their presence / absence affects customer satisfaction:
Requires customer-research input (survey or interview) to populate categories defensibly. Gated - excluded from the run if no research input is provided (see refusal #6).
deliver-roadmap (when shipped; rank, then sequence), deliver-launch-checklist (Must-Have items become launch criteria), sprint-planning workflowsdevelop-solution-brief, define-opportunity-tree, define-hypothesis, discover-interview-synthesisutility-pm-critic (challenges assumed inputs, framework applicability, and divergence explanations)Use the template in references/TEMPLATE.md to structure the output. See references/EXAMPLE.md for a complete worked multi-framework run.
Before finalizing, verify:
references/TEMPLATE.mdreferences/EXAMPLE.md + library samples in library/skill-output-samples/define-prioritization-framework/