name	ln-205-market-researcher
description	Research market conditions, competitors, trends, customer profiles via WebSearch/Ref/Context7. Generate analysis documents with RICE/ICE prioritization. Standalone L2 worker for Epic-level planning.

Market Researcher

Research market opportunity before Epic creation. Generates comprehensive analysis documents with feature prioritization.

Purpose & Scope

Research market via WebSearch, MCP Ref, Context7
Generate 7 analysis documents in docs/market/[topic]/
Provide RICE/ICE scoring for feature prioritization
Support strategic decisions before Epic decomposition

When to Use

Use this skill when:

Planning new product/feature with market uncertainty
Entering competitive market (need competitor analysis)
Evaluating market size for investment decisions
Prioritizing features based on market data

Do NOT use when:

Internal tools (no market)
PoC/prototype (no business case yet)
Minor feature updates (overkill)
Market research already exists in docs/market/

Who calls this skill:

User (manual) - before ln-210-epic-coordinator
Future: ln-200-scope-decomposer (optional Phase 0)

Input Parameters

Parameter	Required	Description	Default
topic	Yes	Product/market name to research	-
scope	No	Geographic/industry scope	"global"
goals	No	What decisions to inform	"feature prioritization"
analyses	No	Subset of 6 types to run	"all"

analyses options: competitor, sizing, trends, customer, ocean, all

Output Structure

docs/market/[topic-slug]/
├── competitor_analysis.md      # Top-10 competitors, feature matrix, positioning
├── market_sizing.md            # TAM/SAM/SOM calculations
├── trends.md                   # 5-7 key trends with impact assessment
├── customer_profile.md         # JTBD framework, 2-3 personas
├── ocean_analysis.md           # Blue/Red Ocean, ERRC grid
├── prioritization.md           # RICE/ICE scored feature list
└── summary.md                  # Executive summary, recommendations

Research Tools

Tool	Purpose	Example Query
WebSearch	Market data, competitors, trends	"[topic] market size 2025"
mcp__Ref	Industry reports, whitepapers	"[topic] industry analysis report"
mcp__context7	Technology trends, adoption	"[library] adoption statistics"
Glob	Check existing docs/market/	"docs/market/[topic]/*"

Tool selection by analysis:

Competitor: WebSearch (G2, Capterra, Crunchbase)
Sizing: WebSearch + Ref (Statista, IBISWorld, Gartner)
Trends: WebSearch + Context7 (Google Trends, GitHub, StackOverflow)
Customer: WebSearch (forums, reviews, job postings)
Ocean: Synthesize from above (no new research)

Workflow

Phase 1: Input & Context (5 min)

Objective: Gather input parameters and check existing research.

Process:

Validate input:
- topic (required) - slugify for directory name
- scope (default: global)
- goals (default: feature prioritization)
- analyses (default: all)
Check existing research:
```
Glob: docs/market/[topic-slug]/*
```
- If exists: Ask "Update existing or create new?"
- If new: Continue to Phase 2
Create output directory:
```
mkdir -p docs/market/[topic-slug]/
```

Output: Validated parameters, empty output directory

Phase 2: Competitor Research (10 min)

Objective: Analyze competitive landscape.

Process:

Search competitors:

WebSearch: "[topic] competitors 2025"
WebSearch: "[topic] alternatives comparison"
WebSearch: "[topic] market leaders"

Extract for each competitor (top 10):
- Company name, founded, funding, employees, HQ
- Key features (5-10 most important)
- Pricing model and tiers
- Target customer segment
- Recent news (funding, launches)
Build feature matrix:
- List all unique features across competitors
- Score: Yes / No / Partial for each
- Identify gaps (features no one offers)
Create positioning map:
- X-axis: Feature richness (Basic → Enterprise)
- Y-axis: Price (Low → High)
- Plot competitors + identify white space
Generate: Fill competitor_template.md, save to docs/market/[topic]/competitor_analysis.md

Output: competitor_analysis.md

Phase 3: Market Sizing (10 min)

Objective: Calculate TAM/SAM/SOM with methodology.

Process:

Research market size:

WebSearch: "[topic] market size TAM 2025"
WebSearch: "[topic] industry report forecast"
Ref: "[topic] market analysis Gartner Statista"

Calculate TAM (Total Addressable Market):
- Top-down: Industry reports, apply segment %
- Bottom-up: Total customers × Average revenue
- Cross-validate with 2+ sources
Calculate SAM (Serviceable Addressable Market):
- Apply filters: geography, company size, tech fit
- Document each filter with %
Calculate SOM (Serviceable Obtainable Market):
- Realistic market share in 3-5 years
- Factor: competition, budget, team capacity
Project growth:
- CAGR from reports
- Year-by-year forecast
Generate: Fill market_sizing_template.md, save to docs/market/[topic]/market_sizing.md

Output: market_sizing.md

Phase 4: Trend Analysis (8 min)

Objective: Identify 5-7 key trends affecting the market.

Process:

Research trends:

WebSearch: "[topic] trends 2025 2026"
WebSearch: "[topic] future predictions"
Context7: "[related technology] adoption trends"

For each trend (5-7):
- Category: Technology / Market / Regulatory / Customer / Economic
- Impact: High / Medium / Low
- Timeframe: Now / 1-2 years / 3-5 years
- Evidence: 2-3 data points with sources
- Implications: Opportunity + Threat + Action
Build impact matrix:
- X-axis: Timeframe (Now → Future)
- Y-axis: Impact (Low → High)
- Classify: Urgent Action / Strategic Priority / Monitor / Watch
Generate: Fill trend_analysis_template.md, save to docs/market/[topic]/trends.md

Output: trends.md

Phase 5: Customer Profile (10 min)

Objective: Define target customers using JTBD framework.

Process:

Research customer needs:

WebSearch: "[topic] customer segments"
WebSearch: "[topic] user reviews pain points"
WebSearch: "[topic] jobs to be done"

Build JTBD framework:
- Core job statement: "When [situation], I want to [goal], so I can [outcome]"
- Functional jobs: What they need to DO (5 items)
- Emotional jobs: How they want to FEEL (3 items)
- Social jobs: How they want to be PERCEIVED (3 items)
Create personas (2-3):
- Demographics: Role, company size, industry, experience
- Goals: Primary, secondary, tertiary
- Pain points: With severity (Critical/Major/Minor)
- Current solutions: With satisfaction level
- Buying behavior: Authority, process, criteria
Build buying criteria matrix:
- Criteria: Price, features, ease of use, integration, support, security
- Weight % for each persona
Generate: Fill customer_profile_template.md, save to docs/market/[topic]/customer_profile.md

Output: customer_profile.md

Phase 6: Ocean Analysis (7 min)

Objective: Determine Blue/Red Ocean and differentiation strategy.

Process:

Classify ocean type:
- Red Ocean indicators (6): Many competitors, price wars, feature parity, slow growth, high churn, commoditization
- Blue Ocean indicators (6): Unmet needs, new market creation, non-customers, value innovation, low competition, high growth
- Score each indicator Y/N
Build Strategy Canvas:
- Identify 7 key factors industry competes on
- Plot industry average for each
- Identify where to diverge
Apply Four Actions Framework (ERRC):
- Eliminate: What to remove (industry takes for granted)
- Reduce: What to lower below standard
- Raise: What to increase above standard
- Create: What to introduce (never offered)
Analyze non-customers:
- Tier 1: Soon-to-be (on edge of market)
- Tier 2: Refusing (chose against market)
- Tier 3: Unexplored (never considered)
Generate: Fill ocean_analysis_template.md, save to docs/market/[topic]/ocean_analysis.md

Output: ocean_analysis.md

Phase 7: Prioritization & Summary (10 min)

Objective: Score features and generate executive summary.

Process:

Collect features:
- From competitor analysis: Feature matrix gaps
- From customer profile: Unmet needs, pain points
- From trends: Emerging requirements
- From ocean analysis: ERRC Create/Raise items

Score with RICE:

RICE = (Reach × Impact × Confidence) / Effort

Reach: 1-10 (users affected per quarter)
Impact: 0.25-3 (Minimal to Massive)
Confidence: 0.5-1.0 (data quality)
Effort: 1-10 (person-months)

Score with ICE:

ICE = Impact × Confidence × Ease

Impact: 1-10 (business value)
Confidence: 1-10 (certainty)
Ease: 1-10 (implementation simplicity)

Rank features:
- Combined rank = average of RICE rank + ICE rank
- Top 10 with rationale
Generate prioritization.md:
- Fill prioritization_template.md
- Include scoring tables and rationale
Generate summary.md:
- Fill summary_template.md
- Key findings (Market, Competition, Customer, Trends)
- Strategic recommendations (Entry strategy, Product priorities, Positioning)
- Risk assessment
- Next steps

Output: prioritization.md, summary.md

Integration with Ecosystem

Position in workflow:

[User Request] → ln-205-market-researcher
                        ↓
                 docs/market/[topic]/
                        ↓
              ln-210-epic-coordinator (uses in Phase 1.2)
                        ↓
              ln-220-story-coordinator

Dependencies:

WebSearch, mcp__Ref, mcp__context7 (research)
Glob, Write, Bash (file operations)

Downstream usage:

ln-210-epic-coordinator Phase 1 Step 2 (Project Research) can reference docs/market/
Epic description can link to research documents
Feature priorities inform Epic scope

Critical Rules

Source all data - Every number needs source + date
Prefer recent data - 2024-2025, warn if older
Cross-reference - 2+ sources for key metrics (TAM, competitor count)
Time-box strictly - 45-60 min total, skip depth for speed
Confidence levels - Mark High/Medium/Low for estimates
No speculation - Only sourced claims, note gaps
Preserve language - If user asks in Russian, respond in Russian

Definition of Done

All requested analyses completed (default: 6)
All 7 documents generated with no placeholders
Sources cited with dates for all data points
Confidence levels assigned to estimates
RICE/ICE scores calculated for 10+ features
Executive summary includes actionable recommendations
Files saved to docs/market/[topic-slug]/
Total time within 45-60 minute budget

Best Practices

Time Management

Phase 1 (Input): 5 min
Phases 2-6 (Research): 8-10 min each = 40-50 min
Phase 7 (Synthesis): 10 min
Total: 55-65 min

Data Quality

Prefer: Industry reports > News > Blogs
Require: Date on all sources
Validate: Cross-reference TAM/SAM with 2+ sources
Document: Note methodology for all calculations

Research Efficiency

Use parallel WebSearch calls where possible
Cache competitor list for reuse across phases
Skip deep dives if time-constrained
Focus on actionable insights over completeness

Example Usage

Basic usage:

ln-205-market-researcher topic="Document Translation API"

With parameters:

ln-205-market-researcher topic="AI Code Review" scope="enterprise, North America" goals="Series A pitch deck"

Specific analyses only:

ln-205-market-researcher topic="PDF Converter" analyses="competitor,sizing"

Example output:

docs/market/ai-code-review/
├── competitor_analysis.md    # GitHub Copilot, Tabnine, Codeium, Amazon Q...
├── market_sizing.md          # TAM: $5.2B, SAM: $1.2B, SOM: $50M
├── trends.md                 # AI-first development, DevEx focus, security
├── customer_profile.md       # DevOps Lead persona, JTBD: reduce review time
├── ocean_analysis.md         # Red Ocean (crowded), Blue space in security
├── prioritization.md         # #1: Security scanning (RICE: 45)
└── summary.md                # Enter via security niche, enterprise focus

Reference Files

File	Purpose
research_sources.md	Trusted sources by category
competitor_template.md	Competitor analysis output
market_sizing_template.md	TAM/SAM/SOM output
trend_analysis_template.md	Trends output
customer_profile_template.md	JTBD + personas output
ocean_analysis_template.md	Blue/Red Ocean output
prioritization_template.md	RICE/ICE scoring output
summary_template.md	Executive summary output

Version: 1.0.0 Last Updated: 2025-12-22

ln-205-market-researcher

Install Skill

SKILL.md

Market Researcher

Purpose & Scope

When to Use

Input Parameters

Output Structure

Research Tools

Workflow

Phase 1: Input & Context (5 min)

Phase 2: Competitor Research (10 min)

Phase 3: Market Sizing (10 min)

Phase 4: Trend Analysis (8 min)

Phase 5: Customer Profile (10 min)

Phase 6: Ocean Analysis (7 min)

Phase 7: Prioritization & Summary (10 min)

Integration with Ecosystem

Critical Rules

Definition of Done

Best Practices

Time Management

Data Quality

Research Efficiency

Example Usage

Reference Files