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Tam Sizing

Community
Productfculty-aipm
tam-sizing

Use this skill when the user asks about "TAM", "total addressable market", "market size", "how big is this market", "SAM", "SOM", "market sizing", "how large is our opportunity", "market opportunity analysis", or needs to produce a defensible market size estimate for a pitch deck, strategic plan, or investment conversation.

Overview

PublisherProductfculty-aipm
RepositoryPM-Copilot-by-Product-Faculty
Skill nametam-sizing
Stars
80
Forks
34
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Productfculty-aipm on GitHub. Read the source before you install it.

Installation

Install the Tam 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/Productfculty-aipm/PM-Copilot-by-Product-Faculty/tree/main/skills/tam-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/Productfculty-aipm/PM-Copilot-by-Product-Faculty.git /tmp/PM-Copilot-by-Product-Faculty
mkdir -p .claude/skills
cp -r /tmp/PM-Copilot-by-Product-Faculty/skills/tam-sizing .claude/skills/tam-sizing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Tam 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 Tam 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 Tam 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.

TAM / SAM / SOM Sizing

You are helping the user build a defensible market size estimate using the TAM/SAM/SOM framework — then applying the bottom-up sanity check to make sure the numbers are grounded, not aspirational.

Framework: Lean Startup (TAM/SAM/SOM), Lenny Rachitsky (PMF and market size), venture capital sizing standards.

Step 1 — Load Context

Read memory/user-profile.md for product context (stage, segment, business model). Read context/company/competitors.md for competitive market context. If WebSearch is available, use it for market data where needed.

Step 2 — Definitions

Before sizing, establish shared definitions:

TAM (Total Addressable Market): The global revenue opportunity if you captured 100% of the market. This is usually a large number that sets the ceiling — it's the "how big is this problem?" figure.

SAM (Serviceable Addressable Market): The portion of TAM you could realistically reach with your current product and business model. This filters for: segment fit, geographic reach, product scope.

SOM (Serviceable Obtainable Market): The portion of SAM you can realistically capture in the next 3–5 years given your current resources and competitive position. This is the number that matters for business planning.

Step 3 — Top-Down Sizing

Build the TAM from available data:

  • Market research reports (use WebSearch if available)
  • Industry analyst figures
  • Comparable company revenue × implied market share
  • Number of potential buyers × average revenue per account

For SAM: apply realistic filters

  • Which geographies are you targeting?
  • Which company sizes or segments does your product serve?
  • What portion of the TAM has the specific problem you solve?

For SOM: apply competitive reality

  • What market share is realistic for a new entrant in year 1–3?
  • What's your growth rate assumption?
  • How many sales cycles can you run with current capacity?

Step 4 — Bottom-Up Sanity Check

Always build a bottom-up model to validate the top-down number:

Bottom-up = (Number of customers reachable) × (Revenue per customer)

Example:

  • There are 500,000 solo PMs in the US
  • We can realistically reach 10% in year 1 via our GTM channels = 50,000 potential customers
  • Of those, 5% will convert at $19/mo = 2,500 customers × $19 × 12 months = $570K ARR in Year 1

If the bottom-up is dramatically lower than the top-down SAM, the SAM is probably wrong. Reconcile the discrepancy.

Step 5 — Investor vs. Internal Use

For investor presentations:

  • Use the top-down TAM as the aspirational frame: "The global PM tools market is $X billion"
  • Use SAM to show you're realistic: "Our serviceable market — solo PMs and founding PMs — is $X million"
  • Use SOM to show the plan: "We expect to capture $X million of that in year 3"

For internal planning:

  • Lead with the SOM — this is your actual planning number
  • Use bottom-up model as the primary tool
  • Sanity-check against top-down

Step 6 — Output

Produce:

  • TAM / SAM / SOM estimates with methodology and sources
  • Bottom-up model with explicit assumptions
  • Reconciliation: do top-down and bottom-up agree? If not, why?
  • Confidence level: which assumptions are strong, which are guesses?
  • The one data point, if you could get it, that would make this estimate most defensible

If using WebSearch, cite sources for any market data pulled.

Frequently asked questions

What does the Tam Sizing AI skill do?

Use this skill when the user asks about "TAM", "total addressable market", "market size", "how big is this market", "SAM", "SOM", "market sizing", "how large is our opportunity", "market opportunity analysis", or needs to produce a defensible market size estimate for a pitch deck, strategic plan, or investment conversation.

Why use Tam Sizing on TypingMind?

Because you install it once and use it with any model. Tam 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 Tam Sizing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Productfculty-aipm/PM-Copilot-by-Product-Faculty/tree/main/skills/tam-sizing. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Tam 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 Tam Sizing?

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

Is the Tam Sizing AI skill free?

It is published on GitHub by Productfculty-aipm. Check the repository for licensing terms. 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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