smithery/ethical-ai-syndicate

product-vision-synthesizer

Use when defining or refining product vision. Use after initial stakeholder input. Produces vision statement, success metrics, strategic alignment documentation, and elevator pitch.

Installation

$ npx skills add smithery/ethical-ai-syndicate --skill product-vision-synthesizer

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  • skill md SKILL.md 7,833 B
  • docs SUMMARY.md 215 B

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SKILL.md

Product Vision Synthesizer

Overview

Articulate a clear, compelling product vision that aligns stakeholders and guides decision-making. Synthesizes inputs from strategy, market research, and user needs into actionable vision artifacts.

Core principle: A good vision inspires action and enables autonomous decision-making. If teams can't use it to make tradeoffs, it's too vague.

When to Use

  • Starting a new product or major initiative
  • Aligning stakeholders on product direction
  • Onboarding new team members
  • Making scope or priority decisions
  • Annual/quarterly vision refresh

Output Format

product_vision:
  product_name: "[Name]"
  version_date: "[YYYY-MM-DD]"
  
  vision_statement:
    one_liner: "[Single sentence vision]"
    expanded: "[2-3 sentence elaboration]"
  
  elevator_pitch:
    for: "[Target user]"
    who: "[Has this need/problem]"
    the: "[Product name]"
    is_a: "[Product category]"
    that: "[Key benefit]"
    unlike: "[Competitor/alternative]"
    our_product: "[Key differentiator]"
  
  target_users:
    primary:
      persona: "[Name]"
      description: "[Who they are]"
      goals: ["[Goal 1]", "[Goal 2]"]
      pain_points: ["[Pain 1]", "[Pain 2]"]
    secondary:
      - persona: "[Name]"
        relationship: "[How they interact with product]"
  
  problem_statement:
    current_state: "[How things work today]"
    pain_points: ["[Pain 1]", "[Pain 2]"]
    cost_of_problem: "[Quantified impact]"
    desired_state: "[How things should work]"
  
  value_proposition:
    functional: "[What the product does]"
    emotional: "[How it makes users feel]"
    economic: "[Business value delivered]"
  
  success_metrics:
    north_star:
      metric: "[Primary success metric]"
      current: "[Baseline]"
      target: "[Goal]"
      timeframe: "[When]"
    supporting:
      - metric: "[Metric name]"
        target: "[Value]"
        rationale: "[Why this metric]"
  
  strategic_alignment:
    company_strategy: "[How this supports company goals]"
    portfolio_fit: "[Relationship to other products]"
    competitive_positioning: "[Market position]"
  
  scope_boundaries:
    in_scope:
      - "[What we will do]"
    out_of_scope:
      - "[What we explicitly won't do]"
    future_consideration:
      - "[What we might do later]"
  
  key_assumptions:
    - assumption: "[What we believe to be true]"
      validation: "[How we'll verify]"
      risk_if_wrong: "[Impact if incorrect]"
  
  decision_principles:
    - principle: "[Guiding principle for tradeoffs]"
      example: "[How to apply it]"

Vision Statement Framework

The One-Liner Formula

[Product] enables [target user] to [achieve outcome] by [unique approach].

Examples:

  • "Slack enables distributed teams to collaborate seamlessly by bringing all communication into searchable channels."
  • "Stripe enables internet businesses to accept payments effortlessly by abstracting away payment infrastructure complexity."

Vision Quality Checklist

Attribute Test Example
Inspiring Does it motivate the team? "Transform how..." vs "Build a tool that..."
Clear Can anyone understand it? No jargon or buzzwords
Directional Does it guide decisions? "Focus on speed" enables tradeoffs
Achievable Is it realistic? Ambitious but not fantasy
Measurable Can you tell if you've achieved it? Ties to success metrics

Elevator Pitch Template

The Geoffrey Moore template:

For [target customer]
Who [statement of need or opportunity]
The [product name]
Is a [product category]
That [key benefit, reason to buy]
Unlike [primary competitive alternative]
Our product [statement of primary differentiation]

Example:

For B2B SaaS companies with 10-50 employees who lose 30% of customers in the first 90 days due to poor onboarding, ChurnBuster is a customer success platform that reduces early churn through personalized intervention. Unlike generic analytics tools, ChurnBuster combines behavioral signals with automated engagement workflows.

Success Metrics Framework

North Star Metric

The single metric that best captures value delivered:

Product Type Example North Star
Marketplace Transactions completed
SaaS Weekly active users
Content Time spent engaging
E-commerce Purchase frequency
Productivity Tasks completed

Supporting Metrics

supporting_metrics:
  acquisition:
    - metric: "New user signups"
      target: "1,000/month"
  activation:
    - metric: "Complete onboarding"
      target: "60% of signups"
  engagement:
    - metric: "DAU/MAU ratio"
      target: ">25%"
  retention:
    - metric: "30-day retention"
      target: ">40%"
  revenue:
    - metric: "MRR growth"
      target: "10% month-over-month"

Problem Statement Structure

Current State

current_state:
  who: "Operations analysts at mid-size banks"
  what_they_do: "Manually match trade confirmations to internal records"
  how_long: "2-3 hours per day"
  pain_points:
    - "Repetitive, low-value work"
    - "Error-prone manual process"
    - "Settlement delays from mismatches"
  cost:
    time: "1,500 hours/year per analyst"
    errors: "2% mismatch rate causing settlement fails"
    money: "$50K/year in failed settlement penalties"

Desired State

desired_state:
  experience: "Analysts review only exceptions, not every confirmation"
  outcome: "95% auto-match rate with human oversight"
  benefit: "Redirect analyst time to complex cases"
  measurement: "Same throughput with 60% less manual effort"

Decision Principles

Help teams make autonomous decisions:

Principle Tradeoff Guidance
"Speed over perfection" Launch MVP, iterate later
"Enterprise-grade reliability" Take time for testing, don't cut corners
"Self-service first" Build features users can discover, minimize support
"Mobile-native experience" Optimize for mobile even if web suffers

Applying Principles:

decision_principles:
  - principle: "Simplicity over feature richness"
    example: |
      When choosing between adding a complex feature 
      and improving an existing simple one, improve the existing.
    
  - principle: "Data-informed, not data-driven"
    example: |
      Metrics guide but don't dictate. User research 
      and judgment matter when data is inconclusive.

Common Mistakes

Mistake Problem Fix
Too vague "Make users happy" Specific outcomes
Too narrow Feature, not vision Lift to outcome level
No boundaries Everything is in scope Explicit out-of-scope
No metrics Can't measure success Define north star
Buzzword-laden "AI-powered synergy" Plain language
Static Never updated Quarterly refresh

Vision Review Cadence

Trigger Action
Quarterly Review metrics, adjust if needed
New strategy Realign to company direction
Market shift Assess competitive positioning
User feedback Validate assumptions
Team confusion Clarify and communicate

Output Checklist

  • Vision statement is one inspiring sentence
  • Elevator pitch follows template structure
  • Target users are specific, not generic
  • Problem is quantified with cost
  • North star metric defined
  • Strategic alignment documented
  • Scope boundaries explicit
  • Decision principles actionable