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Structured market analysis with TAM/SAM/SOM sizing, trends, and competitive landscape via WebSearch, producing investor-grade cited reports. Triggers on: "market size", "TAM SAM SOM", "market opportunity", "industry analysis", "how big is the market", "market trends". NOT for
Claude Code
$ npx -y skills add Mathews-Tom/armory --skill market-analyzer --agent claude-code
Codex
$ npx skills add Mathews-Tom/armory --skill market-analyzer -a codex -y
Cursor
$ npx skills add Mathews-Tom/armory --skill market-analyzer -a cursor -y
Gemini CLI
$ npx skills add Mathews-Tom/armory --skill market-analyzer -a gemini-cli -y
GitHub Copilot
$ npx skills add Mathews-Tom/armory --skill market-analyzer -a github-copilot -y
OpenCode
$ npx skills add Mathews-Tom/armory --skill market-analyzer -a opencode -y
Windsurf
$ npx skills add Mathews-Tom/armory --skill market-analyzer -a windsurf -y
name: market-analyzer description: 'Structured market analysis with TAM/SAM/SOM sizing, trends, and competitive landscape via WebSearch, producing investor-grade cited reports. Triggers on: "market size", "TAM SAM SOM", "market opportunity", "industry analysis", "how big is the market", "market trends". NOT for financial modeling or pricing.' metadata: version: 1.0.1 category: research tags: [market-sizing, tam-sam-som, trends, industry] difficulty: intermediate phase: define
Produces structured market analysis reports: sizes the addressable market using top-down and bottom-up methods, identifies growth trajectories and adoption stages, segments customers, and assesses timing. Every estimate cites a data source or states its assumption explicitly.
| File | Contents | Load When | | ------------------------------ | ------------------------------------------------------------------ | --------- | | `references/tam-sam-som.md` | TAM/SAM/SOM definitions, calculation formulas, common mistakes | Always | | `references/trend-analysis.md` | Trend categorization framework, adoption lifecycle, timing signals | Always | | `references/market-sizing.md` | Data sources, estimation techniques, confidence framework | Always |
1. **Classify the input** — Determine whether the subject is a product idea, feature, market category, or industry vertical. 2. **Extract key attributes:**
3. **Clarify gaps** — If critical context is missing (target customer, geography, or value proposition), ask 3-5 targeted clarifying questions before proceeding.
Use WebSearch to gather quantitative market data:
1. **Industry reports** — Search for market size reports from Statista, Grand View Research, Fortune Business Insights, IBISWorld, and similar aggregators. 2. **Growth rates** — Identify CAGR (Compound Annual Growth Rate) for the relevant market and adjacent segments. 3. **Funding signals** — Search Crunchbase, PitchBook coverage, and venture capital trends in the space. 4. **Consumer trends** — Google Trends data, social media volume, and news sentiment. 5. **Academic research** — Search Semantic Scholar for relevant market studies, adoption research, and behavioral economics papers. 6. **Government/public data** — Census Bureau, BLS, World Bank, OECD datasets for demographic and economic baselines.
For each data point, record the source, publication date, and methodology (if available).
Apply both estimation approaches and cross-validate:
**Top-down (from total industry):**
TAM = Total industry revenue or total potential buyers x average revenue per buyer SAM = TAM x % addressable by geography, segment, and channel SOM = SAM x realistic capture rate (year 1-3)
**Bottom-up (from unit economics):**
Reachable customers = Identified target accounts or users in reachable channels SOM = Reachable customers x conversion rate x average revenue per customer SAM = SOM scaled to full serviceable segment (remove channel constraints) TAM = SAM scaled to total market (remove geographic/segment constraints)
Cross-validate the two approaches. If they diverge by more than 3x, investigate the discrepancy and document the reason.
Evaluate four dimensions:
1. **Market growth trajectory** — Classify as emerging (pre-revenue), growing (CAGR > 10%), mature (CAGR 0-5%), or declining (negative CAGR). 2. **Technology adoption stage** — Map to Rogers curve: innovators (< 2.5%), early adopters (2.5-16%), early majority (16-50%), late majority (50-84%), laggards (> 84%). 3. **Regulatory environment** — Identify tailwinds (subsidies, mandates) and headwinds (restrictions, compliance costs). 4. **Macro trends** — Economic conditions, demographic shifts, technological enablers that accelerate or hinder the market.
Identify 2-5 distinct customer segments:
Produce the structured output below.
## Market Analysis: {Subject}
### Executive Summary
**Market Opportunity Score: {1-5}/5**
{2-3 sentence summary of the opportunity, key market size, and timing assessment.}
### TAM / SAM / SOM
| Level | Value | Methodology | Confidence |
|-------|-------|-------------|------------|
| TAM | ${amount} | {Top-down / Bottom-up / Both} | {High/Medium/Low} |
| SAM | ${amount} | {methodology summary} | {High/Medium/Low} |
| SOM (Year 1) | ${amount} | {methodology summary} | {High/Medium/Low} |
| SOM (Year 3) | ${amount} | {methodology summary} | {High/Medium/Low} |
**Top-down calculation:**
{Step-by-step derivation with sources}
**Bottom-up calculation:**
{Step-by-step derivation with sources}
**Cross-validation:**
{Comparison of approaches, explanation of any divergence}
### Market Trends
| Dimension | Assessment | Evidence |
|-----------|-----------|----------|
| Growth trajectory | {Emerging/Growing/Mature/Declining} | {CAGR, data source} |
| Adoption stage | {Innovators/Early Adopters/Early Majority/Late Majority} | {penetration %, signal} |
| Regulatory | {Tailwind/Neutral/HeadCurated, production-grade skills, agents, hooks, rules, commands, utilities, and presets for AI coding agents. No magic, no demos — battle-tested workflows built for developers who use AI seriously.
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