market-sizing-analysis

market-sizing-analysis is a skill for Claude Code, Codex from rmyndharis/antigravity-skills. It costs 58 tokens per session (2,768 once invoked), scanned A, original, MIT.

A guide to estimating the size of a market using TAM, SAM, and SOM—the total, reachable, and realistically obtainable portions of an opportunity.

In plain words
What is it for?
It supports top-down, bottom-up, and willingness-to-pay analyses for strategy, business planning, and fundraising.
Why use it?
It helps startups and businesses replace broad market claims with estimates grounded in customers, segments, pricing, and evidence.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It supports top-down, bottom-up, and willingness-to-pay analyses for strategy, business planning, and fundraising.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/rmyndharis/antigravity-skills/market-sizing-analysis
About the project

Antigravity Skill Vault is a collection of reusable Agent Skills for Google Antigravity, covering software development, operations, security, and business work. It is for people who want Antigravity agents to follow specialized expertise, personas, and structured workflows. The catalogue skills are entries from this collection.

rmyndharis/antigravity-skills · 1,529 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add rmyndharis/antigravity-skills --skill market-sizing-analysis
Clone the repo
git clone --depth 1 https://github.com/rmyndharis/antigravity-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for market-sizing-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/rmyndharis/antigravity-skills/market-sizing-analysis/github.svg)](https://agentmods.dev/skills/rmyndharis/antigravity-skills/market-sizing-analysis)
Your own site
<a href="https://agentmods.dev/skills/rmyndharis/antigravity-skills/market-sizing-analysis"><img src="https://agentmods.dev/badge/skills/rmyndharis/antigravity-skills/market-sizing-analysis/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for market-sizing-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/rmyndharis/antigravity-skills/market-sizing-analysis"><img src="https://agentmods.dev/badge/skills/rmyndharis/antigravity-skills/market-sizing-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,768 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00058 $0.02768
Opus 5 $0.00029 $0.01384
Sonnet 5 $0.00012 $0.00554
Haiku 4.5 $0.00006 $0.00277

Measured 8d ago against content hash 3a83a1047cb4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

market-sizing-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

2 near-identical copies found in the catalogue:

skills/market-sizing-analysis/SKILL.md · 421 lines

How it starts

The opening of the file, as written. The whole thing — 421 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Market Sizing Analysis

Comprehensive market sizing methodologies for calculating Total Addressable Market (TAM), Serviceable Available Market (SAM), and Serviceable Obtainable Market (SOM) for startup opportunities.

Use this skill when

  • Working on market sizing analysis tasks or workflows
  • Needing guidance, best practices, or checklists for market sizing analysis

Do not use this skill when

  • The task is unrelated to market sizing analysis
  • You need a different domain or tool outside this scope

Instructions

  • Clarify goals, constraints, and required inputs.
  • Apply relevant best practices and validate outcomes.
  • Provide actionable steps and verification.

Overview

Market sizing provides the foundation for startup strategy, fundraising, and business planning. Calculate market opportunity using three complementary methodologies: top-down (industry reports), bottom-up (customer segment calculations), and value theory (willingness to pay).

Core Concepts

The Three-Tier Market Framework

TAM (Total Addressable Market)

  • Total revenue opportunity if achieving 100% market share
  • Defines the universe of potential customers
  • Used for long-term vision and market validation
  • Example: All email marketing software revenue globally

SAM (Serviceable Available Market)

  • Portion of TAM targetable with current product/service
  • Accounts for geographic, segment, or capability constraints
  • Represents realistic addressable opportunity
  • Example: AI-powered email marketing for e-commerce in North America

SOM (Serviceable Obtainable Market)

  • Realistic market share achievable in 3-5 years
  • Accounts for competition, resources, and market dynamics
  • Used for financial projections and fundraising
  • Example: 2-5% of SAM based on competitive landscape

When to Use Each Methodology

Top-Down Analysis

  • Use when established market research exists
  • Best for mature, well-defined markets
  • Validates market existence and growth
  • Starts with industry reports and narrows down

Read the full file on GitHub · 421 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 421 lines · 58 tokens per session scan A 3a83a1047cb4

Subscribe to this mod's changes

market-sizing-analysis is a skill published in the GitHub repository rmyndharis/antigravity-skills (1,529 stars, last pushed 1mo ago), licensed MIT. It adds 58 tokens to every session and 2,768 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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