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.
npx skills add atypica-ai/marketing-skills --skill market-sizinggit clone --depth 1 https://github.com/atypica-ai/marketing-skillsWrote 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.
[](https://agentmods.dev/skills/atypica-ai/marketing-skills/market-sizing)<a href="https://agentmods.dev/skills/atypica-ai/marketing-skills/market-sizing"><img src="https://agentmods.dev/badge/skills/atypica-ai/marketing-skills/market-sizing/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.
<a href="https://agentmods.dev/skills/atypica-ai/marketing-skills/market-sizing"><img src="https://agentmods.dev/badge/skills/atypica-ai/marketing-skills/market-sizing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00072 | $0.05007 |
| Opus 5.5 | $0.00029 | $0.02003 |
| Sonnet 5.5 | $0.00014 | $0.01001 |
| Haiku 4.5 | $0.00007 | $0.00501 |
Grade A, and why
market-sizing 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 391 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TAM / SAM / SOM Market Sizing
Produce both a bottom-up and a top-down analysis for every engagement. Both methods are required — they serve different purposes and must be reconciled. The goal is a defensible, sourced output — not a fast estimate.
When to use this skill
Trigger on any prompt that contains:
- "TAM", "SAM", "SOM", or "market size"
- "How big is the market for X"
- "Total addressable market", "serviceable market", "obtainable market"
- "Market sizing for [product/company]"
- Investor deck context requiring market opportunity quantification
Loading examples
Before calculating, check the examples/ directory for a file matching the product's category. Load the closest match to calibrate data sources, filter logic, and ACV anchors before you begin.
| File | Use when product is... |
|---|---|
examples/b2b-saas.md |
Software / AI tool sold to businesses |
examples/b2c-consumer-brand.md |
Consumer packaged goods, DTC brands, subscriptions |
examples/b2b-physical.md |
Physical goods or materials sold to businesses |
If no exact match exists, load the closest file and adapt.
Pre-flight: Classify the product before doing anything else
Before searching or calculating, classify the product along these two axes. The classification directly determines which data sources to use and which pricing method applies.
Axis 1 — Business model
| Code | Type | Revenue unit | Pricing anchor |
|---|---|---|---|
| B2B-SaaS | Software sold to businesses | Annual contract (ACV) | 10–20% of economic value created |
| B2B-Physical | Physical goods sold to businesses | Per-unit price × annual volume | Gross margin benchmarks by industry |
| B2C-Brand | Consumer product (any category) | Revenue per customer per year | Avg. purchase price × purchase frequency |
| B2C-Subscription | Consumer subscription | Monthly/annual subscription fee | Stated price or comp pricing |
| Marketplace/Platform | Takes % of GMV | Take rate × GMV | Industry take rate benchmarks |
What ships with it
3 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.
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.
- 2mo ago First seen · 391 lines · 72 tokens per session scan A 7b11ea46045e
market-sizing is a skill published in the GitHub repository atypica-ai/marketing-skills (45 stars, last pushed 7mo ago), licensed MIT. It adds 72 tokens to every session and 5,007 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-30.
market-sizing compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| market-sizingatypica-ai/marketing-skills | Skill | 45 | 7mo ago | MIT | A | 72 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |