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Market Sizing

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yonatangross
market-sizing

TAM/SAM/SOM market sizing with top-down and bottom-up estimation methods, cross-validation of assumptions, and divergence reconciliation. Generates investor-ready materials with growth projections and confidence intervals. Use when estimating addressable markets, validating opportunity size, or preparing pitch deck market slides.

Overview

Publisheryonatangross
Repositoryorchestkit
Skill namemarket-sizing
Stars
298
Forks
35
Bundled files
4
LicenseMIT
Links
  • 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.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by yonatangross 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.

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/yonatangross/orchestkit/tree/main/plugins/ork/skills/market-sizing
  4. 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.
2

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/yonatangross/orchestkit.git /tmp/orchestkit
mkdir -p .claude/skills
cp -r /tmp/orchestkit/plugins/ork/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.

Market Sizing

TAM/SAM/SOM framework for estimating addressable market and validating opportunity size.

Definitions

MetricDefinitionQuestion It Answers
TAMTotal Addressable Market — everyone who could possibly buy"What's the theoretical ceiling?"
SAMServiceable Addressable Market — segment you can actually reach"What can we realistically target?"
SOMServiceable Obtainable Market — realistic share in 3 years"What will we actually capture?"
+-------------------------------------------------------+
|                         TAM                            |
|  +---------------------------------------------------+ |
|  |                      SAM                           | |
|  |  +-----------------------------------------------+| |
|  |  |                   SOM                          || |
|  |  +-----------------------------------------------+| |
|  +---------------------------------------------------+ |
+-------------------------------------------------------+

When to Use Top-Down vs. Bottom-Up

MethodUse WhenRisk
Top-DownIndustry reports exist; investor pitch; quick estimateOverestimates SOM
Bottom-UpSales capacity known; pricing validated; more credibleMore work; requires assumptions
Both (recommended)High-stakes decisions; fundraising; board decksCross-validate to build confidence

Always cross-validate both methods and reconcile within 20%. If they diverge by more than that, revisit your assumptions.

Quick Formulas

Top-Down
  TAM = (# potential customers) × (annual value per customer)
  SAM = TAM × (% your solution can address)
  SOM = SAM × (realistic market share % in 3 years)

Bottom-Up
  SOM = (# customers you can acquire) × (average deal size)
  SAM = SOM / (your expected market share %)
  TAM = SAM / (your segment as % of total market)

Example: AI Code Review Tool

markdown
## Market Sizing: AI Code Review Tool

### Top-Down

TAM
- Global developers: 28M
- Using code review tools: 60% → 16.8M
- Average annual spend: $300/developer
- TAM = $5.04B

SAM
- Enterprise only (>500 employees): 8M developers
- Willing to pay premium: 40% → 3.2M
- SAM = $960M

SOM
- Sales capacity supports ~$15M ARR (Year 3)
- Realistic market share: 2%
- Unconstrained SOM = $960M × 2% = $19.2M
- Constrained SOM = min($19.2M, $15M) = $15M

### Bottom-Up
- Target accounts Year 1: 50 enterprise deals
- Average ACV: $100K
- Year 1 ARR: $5M
- Year 3 (3× growth): $15M ARR → SOM = $15M

### Reconciled SOM: $15M (confirmed by both methods)

SOM Constraint Model

Do not report an unconstrained SOM. Always apply real-world limits:

SOM constraints:
  Sales capacity:       supports $15M ARR max
  Competitive pressure: 5 strong incumbents → −20% market share
  Go-to-market reach:   70% of SAM reachable with current channels

Conservative SOM = min(
  SAM × target_share%,
  sales_capacity_ceiling,
  SAM × gtm_reach% × target_share%
)

Confidence Levels

ConfidenceEvidence Required
HIGHMultiple corroborating sources, data < 2 years old
MEDIUMSingle authoritative source, 1-2 years old
LOWExtrapolated, heavy assumptions, data > 2 years old

Always label each number with its confidence level in deliverables.

Common Mistakes

MistakeCorrection
TAM = "everyone on earth"Define a specific, bounded customer segment
SOM = 10% of a billion-dollar marketApply actual sales capacity and GTM constraints
Single method onlyCross-validate top-down and bottom-up
Old dataUse sources < 2 years old; flag if older
Ignoring competitionSOM must account for incumbents' share

References

Related Skills

  • ork:competitive-analysis — Understand competitive dynamics that constrain SOM
  • ork:business-case — Build financial justification once opportunity is sized
  • ork:product-frameworks — Full product strategy toolkit

Version: 1.0.0

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Market Sizing AI skill do?

TAM/SAM/SOM market sizing with top-down and bottom-up estimation methods, cross-validation of assumptions, and divergence reconciliation. Generates investor-ready materials with growth projections and confidence intervals. Use when estimating addressable markets, validating opportunity size, or preparing pitch deck market slides.

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/yonatangross/orchestkit/tree/main/plugins/ork/skills/market-sizing. TypingMind reads its SKILL.md and bundles its files 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 yonatangross 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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