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 mshadmanrahman/pm-pilot --skill market-sizinggit clone --depth 1 https://github.com/mshadmanrahman/pm-pilotWrote 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/mshadmanrahman/pm-pilot/market-sizing)<a href="https://agentmods.dev/skills/mshadmanrahman/pm-pilot/market-sizing"><img src="https://agentmods.dev/badge/skills/mshadmanrahman/pm-pilot/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/mshadmanrahman/pm-pilot/market-sizing"><img src="https://agentmods.dev/badge/skills/mshadmanrahman/pm-pilot/market-sizing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00053 | $0.01211 |
| Opus 5.5 | $0.00021 | $0.00484 |
| Sonnet 5.5 | $0.00011 | $0.00242 |
| Haiku 4.5 | $0.00005 | $0.00121 |
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 1mo 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 — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Market Sizing
Produces a structured TAM/SAM/SOM market sizing analysis using web research, industry data, and bottom-up calculations.
When to Activate
- User says "calculate TAM", "size the market", "market opportunity"
- User asks "how big is the market for X?"
- User needs market sizing for a pitch deck, PRD, or business case
Input
Required:
- Product/service description: What is being sized
- Target customer: Who buys this
Optional:
- Geography: Default is global
- Time horizon: Default is current year + 5-year projection
- Methodology preference: top-down, bottom-up, or both (default: both)
Execution
Context Check
Before sizing, read context/product.md and context/competitors.md if they exist. Existing product positioning and competitive landscape inform market definition and assumptions. After completing the analysis, offer to update context/competitors.md with market landscape findings.
Step 1: Define the Market
Clarify with the user if ambiguous:
- What problem is being solved?
- Who are the target customers (segment, size, industry)?
- What is the product/service category?
- What is the geographic scope?
Step 2: Research (Parallel)
Use web search tools to gather data from multiple sources:
| Data Type | Sources to Search |
|---|---|
| Industry reports | Gartner, Forrester, IDC, Statista, Grand View Research |
| Company data | Public filings, earnings calls, analyst reports |
| Customer data | Census data, industry associations, trade publications |
| Competitive landscape | Crunchbase, PitchBook, competitor pricing pages |
| Growth rates | Historical CAGR, analyst projections |
Step 3: Calculate TAM (Two Methods)
Top-Down:
- Find total market category size from research reports
- Document source, year, and methodology
- Apply growth rate to current year if data is older
Bottom-Up:
- Count total potential customers in target segment
- Determine average annual revenue per customer (pricing research)
- TAM = Total Customers x Annual Revenue per Customer
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.
- 1mo ago First seen · 147 lines · 53 tokens per session scan A cb53c15703df
market-sizing is a skill published in the GitHub repository mshadmanrahman/pm-pilot (22 stars, last pushed 23d ago), licensed MIT. It adds 53 tokens to every session and 1,211 once invoked, about $0.0002 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.
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dev-debug
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