skills/prioritization-advisor/SKILL.md
Choose a prioritization framework based on stage, team context, and stakeholder needs. Use when deciding between RICE, ICE, value/effort, or another scoring approach.
npx skillsauth add locus-taxy/locus-SD-toolkit prioritization-advisorInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Guide product managers in choosing the right prioritization framework by asking adaptive questions about product stage, team context, decision-making needs, and stakeholder dynamics. Use this to avoid "framework whiplash" (switching frameworks constantly) or applying the wrong framework (e.g., using RICE for strategic bets or ICE for data-driven decisions). Outputs a recommended framework with implementation guidance tailored to your context.
This is not a scoring calculator—it's a decision guide that matches prioritization frameworks to your specific situation.
Common frameworks and when to use them:
Scoring frameworks:
Strategic frameworks:
Contextual frameworks:
Use workshop-facilitation as the default interaction protocol for this skill.
It defines:
Other (specify) when useful)This file defines the domain-specific assessment content. If there is a conflict, follow this file's domain logic.
This interactive skill asks up to 4 adaptive questions, offering 3-4 enumerated options at each step.
Agent asks: "What stage is your product in?"
Offer 4 enumerated options:
Or describe your product stage (new idea, growth mode, established, etc.).
User response: [Selection or custom]
Agent asks: "What's your team and stakeholder environment like?"
Offer 4 enumerated options:
Or describe your team/stakeholder context.
User response: [Selection or custom]
Agent asks: "What's the primary challenge you're trying to solve with prioritization?"
Offer 4 enumerated options:
Or describe your specific challenge.
User response: [Selection or custom]
Agent asks: "How much data do you have to inform prioritization?"
Offer 3 enumerated options:
Or describe your data situation.
User response: [Selection or custom]
After collecting responses, the agent recommends a framework:
# Prioritization Framework Recommendation
**Based on your context:**
- **Product Stage:** [From Q1]
- **Team Context:** [From Q2]
- **Decision-Making Need:** [From Q3]
- **Data Availability:** [From Q4]
---
## Recommended Framework: [Framework Name]
**Why this framework fits:**
- [Rationale 1 based on Q1-Q4]
- [Rationale 2]
- [Rationale 3]
**When to use it:**
- [Context where this framework excels]
**When NOT to use it:**
- [Limitations or contexts where it fails]
---
## How to Implement
### Step 1: [First implementation step]
- [Detailed guidance]
- [Example: "Define scoring criteria: Reach, Impact, Confidence, Effort"]
### Step 2: [Second step]
- [Detailed guidance]
- [Example: "Score each feature on 1-10 scale"]
### Step 3: [Third step]
- [Detailed guidance]
- [Example: "Calculate RICE score: (Reach × Impact × Confidence) / Effort"]
### Step 4: [Fourth step]
- [Detailed guidance]
- [Example: "Rank by score; review top 10 with stakeholders"]
---
## Example Scoring Template
[Provide a concrete example of how to use the framework]
**Example (if RICE):**
| Feature | Reach (users/month) | Impact (1-3) | Confidence (%) | Effort (person-months) | RICE Score |
|---------|---------------------|--------------|----------------|------------------------|------------|
| Feature A | 10,000 | 3 (massive) | 80% | 2 | 12,000 |
| Feature B | 5,000 | 2 (high) | 70% | 1 | 7,000 |
| Feature C | 2,000 | 1 (medium) | 50% | 0.5 | 2,000 |
**Priority:** Feature A > Feature B > Feature C
---
## Alternative Framework (Second Choice)
**If the recommended framework doesn't fit, consider:** [Alternative framework name]
**Why this might work:**
- [Rationale]
**Tradeoffs:**
- [What you gain vs. what you lose]
---
## Common Pitfalls with This Framework
1. **[Pitfall 1]** — [Description and how to avoid]
2. **[Pitfall 2]** — [Description and how to avoid]
3. **[Pitfall 3]** — [Description and how to avoid]
---
## Reassess When
- Product stage changes (e.g., PMF → scaling)
- Team grows or reorganizes
- Stakeholder dynamics shift
- Current framework feels broken (e.g., too slow, ignoring important factors)
---
**Would you like implementation templates or examples for this framework?**
Q1 Response: "Early PMF, scaling — Found initial PMF; growing fast; adding features to retain/expand"
Q2 Response: "Cross-functional team, aligned — Product, design, engineering aligned; clear goals"
Q3 Response: "Lack of data-driven decisions — Prioritizing by gut feel; want metrics-based process"
Q4 Response: "Some data — Basic analytics, customer feedback, but no rigorous data collection"
Recommended Framework: RICE (Reach, Impact, Confidence, Effort)
Why this fits:
When to use it:
When NOT to use it:
Implementation:
(Reach × Impact × Confidence) / EffortExample Scoring:
| Feature | Reach | Impact | Confidence | Effort | RICE Score | |---------|-------|--------|------------|--------|------------| | Email reminders | 5,000 | 2 | 70% | 1 | 7,000 | | Mobile app | 10,000 | 3 | 60% | 6 | 3,000 | | Dark mode | 8,000 | 1 | 90% | 0.5 | 14,400 |
Priority: Dark mode > Email reminders > Mobile app (despite mobile app having high Reach/Impact, Effort is too high)
Alternative Framework: ICE (Impact, Confidence, Ease)
Why this might work:
Tradeoffs:
Common Pitfalls:
Q1 Response: "Pre-product/market fit — Searching for PMF; experimenting rapidly"
Q2 Response: "Small team, limited resources — 3 engineers, 1 PM"
Q3 Response: "Too many ideas, unclear which to pursue"
Q4 Response: "Minimal data — New product, no usage metrics"
Recommended Framework: ICE (Impact, Confidence, Ease) or Value/Effort Matrix
Why NOT RICE:
Why ICE instead:
Or Value/Effort Matrix:
Symptom: Pre-PMF startup using weighted scoring with 10 criteria
Consequence: Overhead kills speed. You need experiments, not rigorous scoring.
Fix: Match framework to stage. Pre-PMF = ICE or Value/Effort. Scaling = RICE. Mature = Opportunity Scoring or Kano.
Symptom: Switching frameworks every quarter
Consequence: Team confusion, lost time, no consistency.
Fix: Stick with one framework for 6-12 months. Reassess only when stage/context changes.
Symptom: "Feature A scored 8,000, Feature B scored 7,999, so A wins"
Consequence: Ignores strategic context, judgment, and vision.
Fix: Use frameworks as input, not automation. PM judgment overrides scores when needed.
Symptom: PM scores features alone, presents to team
Consequence: Lack of buy-in, engineering/design don't trust scores.
Fix: Collaborative scoring sessions. PM, design, engineering score together.
Symptom: "We prioritize by who shouts loudest"
Consequence: HiPPO (Highest Paid Person's Opinion) wins, not data or strategy.
Fix: Pick any framework. Even imperfect structure beats chaos.
user-story.md — Prioritized features become user storiesepic-hypothesis.md — Prioritized epics validated with experimentsrecommendation-canvas.md — Business outcomes inform prioritizationSkill type: Interactive
Suggested filename: prioritization-advisor.md
Suggested placement: /skills/interactive/
Dependencies: None (standalone, but informs roadmap and backlog decisions)
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