Skill

tam-analysis

Estimate Total Addressable Market, Serviceable Addressable Market, and Serviceable Obtainable Market for a captured idea. Uses both top-down (industry reports, public stats) and bottom-up (price × users) approaches and reconciles them. Use when the user wants market sizing for an idea.

npx claudepluginhub danielrosehill/claude-code-plugins --plugin business-idea-eval

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This skill uses the workspace's default tool permissions.

Preview

Sizing is always wrong but the discipline is useful. Produce two independent estimates and reconcile.

SKILL.md

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tam-analysis

TAM / SAM / SOM Analysis

Sizing is always wrong but the discipline is useful. Produce two independent estimates and reconcile.

Steps

Read the idea + user context.

Identify the buying unit (end consumer, SMB, mid-market, enterprise, developer, etc.) and the geography (global, region, single country).

Top-down: cite the broadest plausible industry category, look up published market size (use WebSearch / WebFetch for current figures — do not invent), narrow by relevance percentages with explicit reasoning.

Bottom-up: estimate number of buying units × ARPU/ACV × annual purchase frequency. Show every assumption.

Reconcile — if top-down and bottom-up are >5x apart, find the error before reporting.

Define SAM (the slice the company can realistically reach in its initial geography/segment) and SOM (a credible 3-year capture).

Note category dynamics: growing / flat / declining; consolidating / fragmenting.

Output

<workspace_path>/ideas/<slug>/analysis/tam-analysis.md with frontmatter:

--- lens: tam-analysis generated: YYYY-MM-DD tam_usd: <number> sam_usd: <number> som_3y_usd: <number> geography: <scope> ---

Body must include the assumption table for both top-down and bottom-up, plus a one-paragraph confidence note.

Notes

Use WebSearch for current market data; cite sources inline.

If the idea is hyper-niche and no published category exists, document that — and suggest the analogous category that bounds it from above.

Round numbers honestly. Five significant figures is false precision.

TAM / SAM / SOM Analysis

Sizing is always wrong but the discipline is useful. Produce two independent estimates and reconcile.

Steps

Read the idea + user context.
Identify the buying unit (end consumer, SMB, mid-market, enterprise, developer, etc.) and the geography (global, region, single country).
Top-down: cite the broadest plausible industry category, look up published market size (use WebSearch / WebFetch for current figures — do not invent), narrow by relevance percentages with explicit reasoning.
Bottom-up: estimate number of buying units × ARPU/ACV × annual purchase frequency. Show every assumption.
Reconcile — if top-down and bottom-up are >5x apart, find the error before reporting.
Define SAM (the slice the company can realistically reach in its initial geography/segment) and SOM (a credible 3-year capture).
Note category dynamics: growing / flat / declining; consolidating / fragmenting.

Output

<workspace_path>/ideas/<slug>/analysis/tam-analysis.md with frontmatter:

---
lens: tam-analysis
generated: YYYY-MM-DD
tam_usd: <number>
sam_usd: <number>
som_3y_usd: <number>
geography: <scope>
---

Body must include the assumption table for both top-down and bottom-up, plus a one-paragraph confidence note.

Notes

Use WebSearch for current market data; cite sources inline.
If the idea is hyper-niche and no published category exists, document that — and suggest the analogous category that bounds it from above.
Round numbers honestly. Five significant figures is false precision.