market-size

market-size is a command for Claude Code from Aznatkoiny/zAI-Skills. It costs 12 tokens per session (764 once invoked), scanned A, original, MIT.

A command for estimating the size of a market using published data and calculated assumptions.

In plain words
What is it for?
Use it to build top-down and bottom-up estimates, document sources, calculate customer spending, and compare scenarios.
Why use it?
It provides a structured way to estimate an opportunity when no single reliable market figure exists.

Command for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the consulting-toolkit plugin — 1 skill, 17 commands, 5 agents shipped together

Good fit Use it to build top-down and bottom-up estimates, document sources, calculate customer spending, and compare scenarios.

Compare 6 commands from other repositories ↓
Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code
/plugin marketplace add Aznatkoiny/zAI-Skills
Claude Code
/plugin install consulting-toolkit

Made for: Claude Code.

Or install consulting-toolkit, the plugin that ships this one along with the rest of its 1 skill, 17 commands, 5 agents.

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-size

README.md
[![agentmods](https://agentmods.dev/badge/commands/aznatkoiny/zai-skills/market-size/github.svg)](https://agentmods.dev/commands/aznatkoiny/zai-skills/market-size)
Your own site
<a href="https://agentmods.dev/commands/aznatkoiny/zai-skills/market-size"><img src="https://agentmods.dev/badge/commands/aznatkoiny/zai-skills/market-size/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-size

Your own site · 80×15
<a href="https://agentmods.dev/commands/aznatkoiny/zai-skills/market-size"><img src="https://agentmods.dev/badge/commands/aznatkoiny/zai-skills/market-size.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 12 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 764 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.
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 $0.00012 $0.00764
Opus 5 $0.00006 $0.00382
Sonnet 5 $0.00002 $0.00153
Haiku 4.5 $0.00001 $0.00076

Measured 10d ago against content hash 778ea318ebf6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

market-size 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 10d 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.

consulting-toolkit/commands/market-size.md · 54 lines

What it actually says

You are a senior consultant at a top-tier strategy firm producing partner-review-ready market sizing. Every number must be sourced or explicitly marked as an assumption. The output must be rigorous enough to anchor a board-level investment decision.

Perform a comprehensive market sizing for: $ARGUMENTS

Data sourcing: pull macro context (GDP, CPI, rates) with mcp__financial-intelligence__fin_get_macro_indicators, cited as [FRED, date], and US public players' revenues with mcp__financial-intelligence__fin_get_company_financials, cited as [SEC EDGAR, date], before web searching. Use WebSearch for market reports, private companies, and analyst estimates. If the MCP tools are unavailable, fall back to WebSearch and state so.

  1. TOP-DOWN SIZING — start from the largest credible published figure and apply successive splits to narrow to the target market. Show each step as a chain:

    • Total industry revenue (source) → applicable geography share → relevant segment share → target market
    • Every split factor must have a source or be flagged as an estimate with stated rationale.
  2. BOTTOM-UP SIZING — build from unit economics:

    • Number of potential customers × average spend × purchase frequency
    • Clearly state how you estimated each variable.
    • This approach serves as a cross-check, not just a secondary number.
  3. TRIANGULATE — compare the two approaches. If they diverge by more than 30%, investigate why. Common causes: different scope definitions, outdated top-down data, or overly optimistic bottom-up assumptions. Arrive at a defensible range, not a false-precision point estimate.

  4. SIZE THE LAYERS:

    • TAM: Total addressable market — the full revenue opportunity if 100% market share
    • SAM: Serviceable addressable market — the portion reachable given business model and go-to-market constraints
    • SOM: Serviceable obtainable market — realistic capture given competitive dynamics and ramp time
    • Define each layer specifically for this market, not with generic definitions.

<output_format> Start from the skeleton at ${CLAUDE_PLUGIN_ROOT}/templates/market-sizing.md — it prewires the sizing chains, the TAM/SAM/SOM table, and the assumptions table with its mandatory source column. Structure the deliverable as:

  • Executive summary (3-5 bullets with the headline numbers)
  • Market definition and scoping choices
  • Top-down sizing (show the math step by step)
  • Bottom-up sizing (show the math step by step)
  • Triangulation and reconciliation
  • TAM / SAM / SOM summary table
  • Key assumptions table (assumption | value | source | confidence level)
  • Sensitivity analysis on the 2-3 assumptions that most move the number
  • Sources list </output_format>

<quality_standards>

  • Use web search to find real, current data. Never fabricate or hallucinate numbers.
  • Distinguish clearly between hard data, analyst estimates, and your own calculations.
  • Flag data gaps explicitly rather than papering over them with false precision.
  • Every quantitative claim must have a bracketed source: [Source, Date].
  • Present ranges rather than point estimates where the data warrants it. </quality_standards>

Save output as market-sizing-[topic].md in the working directory.

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. 10d ago First seen · 54 lines · 12 tokens per session scan A 778ea318ebf6

Subscribe to this mod's changes

market-size is a command published in the GitHub repository Aznatkoiny/zAI-Skills (9 stars, last pushed 1mo ago), licensed MIT. It adds 12 tokens to every session and 764 once invoked, about $0.0001 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 2026-08-31.