Framing Opportunity

---
id: prompt-framing-opportunity
type: discovery
phase: framing
name: "Opportunity Articulation"
version: 1.0.0
tags: [framing, opportunity, value-proposition]
lens_rules: [value_over_noise, show_dont_tell, bias_toward_action]
---

# Opportunity Articulation

## Input Requirements
- **Problem statement**: Validated problem statement (from problem framing)
- **User personas**: Who is affected
- **Competitive context**: What alternatives exist
- **Project capabilities**: What the team can realistically deliver

## Instructions

### Step 1: Value Proposition Definition
Define the value proposition across these layers:

| Layer | Description | Our Answer |
|-------|-------------|------------|
| Core benefit | Primary value delivered | |
| Key differentiator | What makes this unique | |
| Emotional payoff | How users feel | |
| Social proof | Why users should trust this | |

### Step 2: Opportunity Statement
Write a structured opportunity statement:

> We believe that [target audience] needs [solution] because [insight]. Unlike [alternatives], we provide [differentiator], which enables [outcome]. We will know we are right when [success metric] reaches [target].

### Step 3: Example Scenarios
Provide 2-3 concrete examples of the opportunity in action:

> **[Example title]**: [User] currently does [current approach]. With our solution, they can [new approach]. The difference is [specific improvement]. For instance, [realistic scenario showing the delta].

### Step 4: Risk-Adjusted Opportunity
- **Best case**: What if everything goes right
- **Expected case**: Most likely outcome
- **Worst case**: What if key assumptions fail
- **Threshold**: Minimum viable outcome that still provides value

### Step 5: Next Action
- **Target artifact**: Opportunity Canvas (`.skillweave/templates/discovery/opportunity-canvas.md`)
- **Suggested next step**: Validate opportunity with target users

## Output Format
Markdown document with value proposition layers table, structured opportunity statement, 2-3 concrete example scenarios, risk-adjusted outcome ranges, and recommended go/no-go criteria.