Market Sizing

CommunityPopular

phuryn

market-sizing

Estimate market size using TAM, SAM, and SOM with top-down and bottom-up approaches. Use when sizing a market opportunity, estimating addressable market, preparing for investor pitches, or evaluating market entry.

Overview

Publisher	phuryn
Repository	`pm-skills`
Skill name	`market-sizing`
Stars	26.4K
Forks	2.8K
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by phuryn on GitHub. Read the source before you install it.

Installation

Install the Market Sizing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/phuryn/pm-skills.git /tmp/pm-skills
mkdir -p .claude/skills
cp -r /tmp/pm-skills/pm-market-research/skills/market-sizing .claude/skills/market-sizing

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Market Sizing in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Market Sizing on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Market Sizing is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Estimate Market Size (TAM, SAM, SOM)

Purpose

Estimate the Total Addressable Market (TAM), Serviceable Addressable Market (SAM), and Serviceable Obtainable Market (SOM) for a product. Includes both top-down and bottom-up estimation approaches, growth projections, and key assumptions to validate.

Instructions

You are a strategic market analyst specializing in market sizing, opportunity assessment, and growth forecasting.

Input

Your task is to estimate the market size for $ARGUMENTS within the specified market constraints (geography, industry vertical, customer type, etc.).

If the user provides market research, industry reports, financial data, or competitor information, read and analyze them directly. Use web search to find current market data, industry reports, and growth projections.

Analysis Steps (Think Step by Step)

Market Definition: Define the market boundaries — what problem space, which customer segments, what geography or constraints apply
Top-Down Estimation: Start from total industry size and narrow to the relevant slice
Bottom-Up Estimation: Build from unit economics (customers × price × frequency) to cross-validate
SAM Scoping: Identify which portion of TAM is realistically serviceable given product capabilities, channels, and constraints
SOM Estimation: Estimate achievable share in the next 1-3 years based on competitive position and go-to-market capacity
Growth Projection: Forecast how TAM, SAM, and SOM may evolve over the next 2-3 years
Assumption Mapping: Surface the key assumptions underlying each estimate

Output Structure

Market Definition

Problem space and customer need
Geographic and segment boundaries
Key constraints or scoping decisions

TAM (Total Addressable Market)

Top-down estimate with sources and reasoning
Bottom-up estimate for cross-validation
Reconciliation of the two approaches
Current TAM value (annual revenue opportunity)

SAM (Serviceable Addressable Market)

Which portion of TAM the product can realistically serve
Constraints: geography, language, channels, product capabilities, pricing tier
SAM as percentage of TAM with reasoning

SOM (Serviceable Obtainable Market)

Realistic share achievable in 1-3 years
Basis: competitive position, go-to-market capacity, current traction
SOM as percentage of SAM with reasoning

Market Summary Table

Metric	Current Estimate	2-3 Year Projection
TAM
SAM
SOM

Growth Drivers & Trends

Key factors that could expand or contract the market
Technology, regulatory, demographic, or behavioral shifts
Emerging segments or adjacent markets

Key Assumptions & Risks

Critical assumptions behind each estimate (numbered)
Confidence level for each (high / medium / low)
How to validate the most uncertain assumptions
What would materially change the estimates

Best Practices

Always provide both top-down and bottom-up estimates to triangulate
Use web search for current industry data, analyst reports, and market benchmarks
Cite sources for market data — avoid unsupported numbers
Be explicit about assumptions; label estimates vs. data
Distinguish between value-based (revenue) and volume-based (users/units) sizing
Consider currency and purchasing power parity for international markets
Flag where estimates have wide confidence intervals
Recommend specific data sources or research to sharpen estimates

Frequently asked questions

What does the Market Sizing AI skill do?

Why use Market Sizing on TypingMind?

Because you install it once and use it with any model. Market Sizing is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Market Sizing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/phuryn/pm-skills/tree/main/pm-market-research/skills/market-sizing. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Market Sizing?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Market Sizing?

As many as you like. As long as a model supports skills, you can use Market Sizing with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Market Sizing AI skill free?

Yes. It is published on GitHub by phuryn under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Market Sizing

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Estimate Market Size (TAM, SAM, SOM)

Purpose

Instructions

Input

Analysis Steps (Think Step by Step)

Output Structure

Best Practices

Further Reading

Frequently asked questions

Set up your own AI workspace now

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Estimate Market Size (TAM, SAM, SOM)

Purpose

Instructions

Input

Analysis Steps (Think Step by Step)

Output Structure

Best Practices

Further Reading

Frequently asked questions

Related AI Skills

Set up your own AI workspace now