Market Sizing Agent
SkillAI & modelsTAM/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.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Market Sizing Agent skill
What this skill tells your AI
The instructions your AI receives, as published by onewave-ai/claude-skills in market-sizing/SKILL.md and read by ahel’s review.
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.
Signals
- GitHub stars
- 291
- Forks
- 46
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
market-sizing-onewave-ai- Source
- github.com/onewave-ai/claude-skills