ln-201-opportunity-discoverer

安装量: 108
排名: #7820

安装

npx skills add https://github.com/levnikolaevich/claude-code-skills --skill ln-201-opportunity-discoverer

Paths: File paths ( shared/ , references/ , ../ln-* ) are relative to skills repo root. If not found at CWD, locate this SKILL.md directory and go up one level for repo root. 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: Invent idea with no analogs Ask 5 people "would you pay?" (they say yes for a hot dog) Build product with round sum Launch with "now let's set up traffic" Discover: no traffic exists, never did No marketer will build funnel for what cold traffic doesn't buy. Traffic-First Principles

Principle
Anti-pattern
1
Traffic exists BEFORE product
Building then searching for traffic
2
No surveys
— measure real search demand
Asking "would you buy?"
3
Existing demand
— launch under what people search
Creating new category
4
One channel, one idea
— no spreading
Testing 5 channels at once
5
KILL early
— fail fast, don't waste time
Scoring all ideas equally
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
Parameter
Required
Description
Default
ideas
No
Comma-separated list
-
context
No
Product description for generation
-
strict
No
Strict KILL thresholds
true
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:
Channel
Signal
Best for
Search/SEO
People Google "[problem] solution"
Info products, tools
YouTube
Tutorial searches exist
Education, how-to
Marketplaces
Category exists (ProductHunt, AppStore)
Apps, plugins
Communities
Active subreddits, forums
Niche products
Paid Ads
Competitors running ads
Proven demand
Outbound
Clear ICP, reachable
B2B high-ticket
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:
Signal
Source
Interpretation
Search volume
Google Keyword Planner, Ahrefs
Direct demand
Trend direction
Google Trends
Growing/declining
Forum activity
Reddit, HackerNews, StackOverflow
Pain level
Competitor traffic
SimilarWeb, SEMrush
Market size
KILL thresholds:
Volume
Verdict
>10K/month
Strong demand
1K-10K/month
Viable niche
<1K/month
KILL
— insufficient demand
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:
Competitors
Index
Ocean
Verdict
0
1
Blue
Opportunity (validate demand exists)
1-2
2
Emerging
Best entry point
3-5
3
Growing
Differentiation needed
6-10
4
Mature
Hard but possible
>10
5
Red
KILL
— commoditized
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:
ARPU
Market type
Viability
>$100/user/mo
Enterprise
High margin
$50-100
Professional
Good
$20-50
Prosumer
Viable
$5-20
Consumer
Volume needed
<$5
Ad-supported
KILL
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:
Factor
Question
Red flag
Tech
Existing skills or need to learn?
New stack
Dependencies
External APIs, partners needed?
Waiting on others
Content
Significant content creation?
Months of writing
Regulations
Legal/compliance requirements?
Licenses, approvals
Team
Solo or need to hire?
Can't start alone
Time estimates:
Weeks
Complexity
Verdict
1-2
Solo, existing skills
Best
2-4
Minor learning curve
Good
4-8
Some new tech
Acceptable
>8
Significant infrastructure
KILL
KILL if:
>8 weeks to MVP — too slow to validate.
Output:
Weeks estimate + blockers
Workflow
Phase 1: Input Processing (2 min)
Parse input:
If
ideas
split comma-separated list
If
context
generate 5-7 ideas via WebSearch If both: combine Validate count: Minimum: 3 ideas Maximum: 10 ideas 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: Calculate composite score: Score = Demand_score + (6 - Competition_index) + Revenue_score + Interest + MVP_score Sort by score descending 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 Ideas Estimated time 3 15-20 min 5 25-35 min 10 50-70 min 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 Traffic first — no traffic channel = no analysis KILL immediately — don't score dead ideas One recommendation — avoid paralysis No surveys — real search data only Interest matters — you'll quit if bored 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 | Reference Files File Purpose filter_criteria.md KILL thresholds for all filters channel_analysis.md Traffic channel identification discovery_template.md Output markdown template MANDATORY READ: shared/references/research_tool_fallback.md Version: 2.0.0 Last Updated: 2026-01-29

返回排行榜