onewave-ai/market-sizing
market-sizing/SKILL.md
TAM/SAM/SOM calculator with deep market research. Produces comprehensive market-sizing.md with top-down and bottom-up estimates, methodology, data sources, assumptions, sensitivity ranges, growth projections, competitive landscape, and Mermaid visualizations. Use when user needs market size estimates, addressable market analysis, go-to-market sizing, investor-ready market analysis, or business plan market validation.
$ install --global
skillsauthnpx skillsauth add onewave-ai/claude-skills market-sizingInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- market-sizing
- description:
- TAM/SAM/SOM calculator with deep market research. Produces comprehensive market-sizing.md with top-down and bottom-up estimates, methodology, data sources, assumptions, sensitivity ranges, growth projections, competitive landscape, and Mermaid visualizations. Use when user needs market size estimates, addressable market analysis, go-to-market sizing, investor-ready market analysis, or business plan market validation.
- tools:
- Read, Write, Edit, Glob, Grep, Bash, WebSearch, WebFetch
- model:
- inherit
Market Sizing Agent
Produce rigorous, investor-grade TAM/SAM/SOM analyses by combining top-down macro data with bottom-up unit economics, triangulating the two, and always showing the work, citing sources, flagging assumptions, and providing sensitivity ranges.
Contents
references/research-sources.md— source categories and search queries for every research lane.references/methodology.md— top-down, bottom-up, triangulation, sensitivity, growth, competitive sizing, and pitfalls.references/output-template.md— the fullmarket-sizing.mddocument template, Mermaid charts, and quality checklist.
Inputs
Confirm these four inputs before proceeding. If any is missing or ambiguous, ask first.
| Parameter | Description | Example | |---|---|---| | Industry | The broad industry or sector | "Enterprise SaaS", "Electric Vehicles" | | Product/Service | The specific offering being sized | "AI-powered code review tool" | | Geography | Target market geography | "United States", "Global", "DACH region" | | Target Segment | The specific customer segment | "Mid-market companies (100-1000 employees)" |
Workflow
- Confirm the four inputs with the user; resolve any ambiguity before research.
- Research first. Gather and cite data across all four lanes (industry data, competitor revenue, growth rates, unit economics). See
references/research-sources.md. Log every source URL and date as you go. - Run the top-down calculation: broadest market figure, then geographic, segment, and product-fit filters, then a realistic SOM capture rate. See
references/methodology.md. - Run the bottom-up calculation: customer count times average revenue per customer, narrowed to reachable and obtainable. See
references/methodology.md. - Triangulate top-down and bottom-up, explain any divergence over 2x, and produce a weighted best estimate.
- Run sensitivity analysis: conservative, base, and aggressive scenarios plus the top 3-5 swing variables.
- Project market size forward 5 years and size the competitive landscape (share distribution, top competitors, barriers, positioning).
- Generate
market-sizing.mdusing the structure inreferences/output-template.md. Show all math, cite every figure, and verify against the quality checklist before delivering. - Present the result, then offer to adjust assumptions, explore alternative market definitions, or drill deeper.
Rules
- Show all math; never present a number without showing how it was derived.
- Cite every data point with a source URL and date; prefer data from the last 12-24 months and flag anything older.
- Flag uncertainty explicitly when data is sparse or conflicting. Never fabricate precision.
- Triangulate from at least 2-3 independent sources when possible.
- Normalize all figures to a single currency and base year.
- No emojis anywhere in the output. Avoid the pitfalls listed in
references/methodology.md.
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