Ln 201 Opportunity Discoverer

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Opportunity Discoverer

Traffic-First approach to finding next growth direction for existing product.

Core Philosophy

Anti-pattern: Idea → Surveys → Product → "where's traffic?" Correct: Traffic → Niche → MVP → Launch under existing demand

The 90% Developer Bug

Most fail because they:

1. Invent idea with no analogs
2. Ask 5 people "would you pay?" (they say yes for a hot dog)
3. Build product with round sum
4. Launch with "now let's set up traffic"
5. Discover: no traffic exists, never did

No marketer will build funnel for what cold traffic doesn't buy.

Traffic-First Principles

Supporting Methodology

Marc Andreessen (pmarca):

"Validate market at practical level — go get paying customers to demonstrate market exists."

Sam Altman (YC):

"Who desperately needs the product? Best answer is going after large part of small market." "Test idea by launching or trying to sell — get letter of intent before code."

Purpose & Scope

• Discover growth direction BEFORE Epic creation
• Filter ideas through sequential KILL funnel
• Output: one recommended idea + one traffic channel
• Position: before ln-210 (Epic Coordinator)

When to Use

Use this skill when:

• Product exists, seeking next growth direction
• Have 3-10 potential ideas/niches
• Want to validate opportunity before committing
• Need to choose ONE channel to focus on

Do NOT use when:

• No product context (greenfield startup)
• Already have validated direction (skip to ln-210)
• Prioritizing existing Stories (use ln-230)

Input Parameters

Input modes:

• ideas="idea1, idea2, idea3" — evaluate list
• context="SaaS for X" — generate ideas from product
• Both — generate + add user ideas

KILL Funnel Pipeline

Ideas pass through 6 sequential filters. Fail any filter = KILL immediately.

Idea → [Traffic?] → [Demand?] → [Competition?] → [Revenue?] → [Interest?] → [MVP?] → SURVIVOR
              ↓           ↓            ↓             ↓            ↓           ↓
            KILL        KILL         KILL          KILL         KILL        KILL

Filter 1: Traffic Channel

Question: Where do people look for this solution?

Research:

WebSearch: "[idea] how people find solutions"
WebSearch: "[idea] customer acquisition channels"

Valid channels:

KILL if: No identifiable channel where people actively look for solution.

Output: Channel name + rationale

Filter 2: Existing Demand

Question: Are people already searching for this?

Research:

WebSearch: "[idea] search volume {current_year}"
WebSearch: "[idea] Google Trends"
WebSearch: "[problem] forum discussions reddit"

Demand signals:

KILL thresholds:

Output: Monthly volume estimate + trend

Filter 3: Competition (Blue/Red Ocean)

Question: Can we enter this market?

Research:

WebSearch: "[idea] competitors {current_year}"
WebSearch: "[idea] alternatives comparison"

Classification:

KILL if: Index 5 (Red Ocean) — too many competitors, race to bottom.

Output: Competitor count + Ocean type

Filter 4: Revenue Potential

Question: Will people pay enough?

Research:

WebSearch: "[idea] pricing SaaS"
WebSearch: "[competitor] pricing plans"
WebSearch: "[idea] willingness to pay"

Revenue indicators:

KILL if: <$20/user — not worth the effort for small team.

Output: Estimated $/user + pricing model

Filter 5: Personal Interest

Question: Will you enjoy building this?

Method: AskUserQuestion — rate 1-5

Rate your interest in building [idea]:
1 = Meh, would do for money only
2 = Low interest
3 = Neutral
4 = Interested
5 = Excited, would build for free

Why this matters:

• Low interest = burnout in 3 months
• High interest = sustained motivation through hard times
• You'll spend 2+ years on this

KILL if: Score 1-2 — you'll quit before PMF.

Output: Score 1-5

Filter 6: MVP-ability

Question: Can you launch in 4 weeks?

Assessment:

Time estimates:

KILL if: >8 weeks to MVP — too slow to validate.

Output: Weeks estimate + blockers

Workflow

Phase 1: Input Processing (2 min)

1. Parse input:

   • If ideas: split comma-separated list
   • If context: generate 5-7 ideas via WebSearch
   • If both: combine

2. Validate count:

   • Minimum: 3 ideas
   • Maximum: 10 ideas

3. Create output directory:

   mkdir -p docs/reference/research/
   

Output: Idea queue (3-10 items)

Phase 2: KILL Funnel (per idea)

Process each idea sequentially through all 6 filters:

FOR each idea:
    Filter 1: Traffic Channel
        IF no channel → KILL, log reason, NEXT idea

    Filter 2: Existing Demand
        IF <1K/month → KILL, log reason, NEXT idea

    Filter 3: Competition
        IF Index 5 → KILL, log reason, NEXT idea

    Filter 4: Revenue
        IF <$20/user → KILL, log reason, NEXT idea

    Filter 5: Interest
        AskUserQuestion for rating
        IF score 1-2 → KILL, log reason, NEXT idea

    Filter 6: MVP-ability
        IF >8 weeks → KILL, log reason, NEXT idea

    → SURVIVOR: add to survivors list

Token efficiency:

• Process ONE idea at a time
• KILL early = less research needed
• Clear context after each idea

Phase 3: Rank Survivors (2 min)

If survivors exist:

1. Calculate composite score:

   Score = Demand_score + (6 - Competition_index) + Revenue_score + Interest + MVP_score
   

2. Sort by score descending

3. Select TOP recommendation

If no survivors:

• Report: "All ideas killed. Rethink direction."
• Show KILL log for learning

Phase 4: Output (2 min)

Generate: docs/reference/research/[YYYY-MM-DD]-discovery.md

Structure:

# Opportunity Discovery: [Date]

## Summary
- Ideas analyzed: X
- Survivors: Y
- Killed: Z

## TOP RECOMMENDATION

**Idea:** [Name]
**Channel:** [Primary channel]
**Why:** [2-3 sentence rationale]

### Key metrics:
- Demand: [volume]/month
- Competition: [Index] [Ocean type]
- Revenue: $[X]/user
- MVP: [X] weeks

## Survivors Table

| Idea | Channel | Demand | Competition | Revenue | Interest | MVP | Score |
|------|---------|--------|-------------|---------|----------|-----|-------|
| ... | ... | ... | ... | ... | ... | ... | ... |

## KILL Log

| Idea | Killed at | Reason |
|------|-----------|--------|
| ... | ... | ... |

## Next Steps
1. Create Epic with ln-210 for top recommendation
2. Focus on [channel] as primary acquisition
3. Target MVP in [X] weeks

Time-Box

Note: KILL funnel is faster than full scoring — bad ideas die early.

Integration

Position in workflow:

Product exists
     ↓
ln-201 (Opportunity Discovery) ← THIS SKILL
     ↓
ln-210 (Epic Coordinator)
     ↓
ln-220 (Story Coordinator)

Dependencies:

• WebSearch (all filters except Interest)
• AskUserQuestion (Interest filter)
• Write, Bash (output)

Critical Rules

1. Traffic first — no traffic channel = no analysis
2. KILL immediately — don't score dead ideas
3. One recommendation — avoid paralysis
4. No surveys — real search data only
5. Interest matters — you'll quit if bored
6. MVP speed — slow launch = slow learning

Example Usage

With ideas:

ln-201-opportunity-discoverer ideas="AI writing tool, code review bot, translation API"

With context:

ln-201-opportunity-discoverer context="B2B developer tools SaaS"

Example output:

# Opportunity Discovery: 2026-01-29

## TOP RECOMMENDATION

**Idea:** Code review bot
**Channel:** SEO (developers search "code review tool")
**Why:** Growing demand (15K/mo), emerging market (3 competitors),
$50/user pricing proven, can MVP in 3 weeks with existing skills.

## KILL Log

| Idea | Killed at | Reason |
|------|-----------|--------|
| AI writing | Competition | Red Ocean (25+ competitors) |
| Translation API | Revenue | Commoditized, <$10/user |

Definition of Done

• Ideas brainstormed from product context and market signals
• KILL funnel applied: each idea passed/killed at each filter stage
• Survivors scored and ranked
• Discovery document generated at docs/reference/research/[YYYY-MM-DD]-discovery.md
• TOP RECOMMENDATION identified with channel + rationale
• KILL Log documents all eliminated ideas with reasons

Reference Files

• MANDATORY READ: shared/references/research_tool_fallback.md

Version: 2.0.0 Last Updated: 2026-01-29