Agent skill · Data & Analytics

discover-market-sizing

Estimate market opportunity (TAM, SAM, SOM) using multiple sizing frameworks (top-down, bottom-up, comparable company, analogous market). Triangulates across frameworks, highlights where they converge and diverge as signal, and produces a calibrated range with source-graded confidence labels. Refuses unbounded fabrications; always offers a labeled lower-confidence path when data is thin. Used for investment cases, go/no-go decisions, and stakeholder pitches.

product-on-purposegithub.com/product-on-purposeGitHub ↗
claude-codecodexApache-2.0
Install
npx skills add product-on-purpose/pm-skills --skill discover-market-sizing --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 5
SKILL.md size: 13 KB
Bundled scripts: none
Version: 1.1.0
Declared author: product-on-purpose
Path: skills/discover-market-sizing/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 518
Language: JavaScript

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 --> # Market Sizing You produce a multi-framework market-sizing meta-analysis covering TAM (Total Addressable Market), SAM (Serviceable Addressable Market), and SOM (Serviceable Obtainable Market). You run all applicable sizing frameworks (top-down, bottom-up, comparable company, analogous market), compare where they converge and diverge, and synthesize a calibrated estimate with a recommendation. Divergence between frameworks is often the most valuable finding. Your job is to produce a defensible artifact and explain the reasoning. ## Identity - Phase skill (discover); Triple Diamond integration - Single-turn lifetime; produces one artifact per invocation - Read-only tools (Read, Grep, WebFetch, WebSearch) if available; no write outside the output artifact - Outputs a markdown document with structured sections ## Core principle **Multi-framework synthesis and epistemic discipline.** Run all applicable frameworks; convergence across methods increases confidence, divergence is a finding to explain. Every dollar figure must trace to (a) a cited public source, (b) an explicitly-stated assumption with reasoni

What's inside
Steps it walks through
  1. Identity
  2. Core principle
  3. When NOT to Use
  4. Inputs
  5. What you produce
  6. 1. Executive summary (3-5 sentences)
  7. 2. Market definition
  8. 3. Top-down sizing
  9. 4. Bottom-up sizing (when data permits)
  10. 5. Multi-framework synthesis
  11. 6. Sensitivity analysis
  12. 7. Key assumptions (explicit)
  13. 8. Confidence and limitations
  14. 9. Next steps (recommendations)
Ships with 4 files
  • HISTORY.md
  • evals/trigger-fixtures.json
  • references/EXAMPLE.md
  • references/TEMPLATE.md
More from pm-skills
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About this skill
What does the discover-market-sizing skill do?

Estimate market opportunity (TAM, SAM, SOM) using multiple sizing frameworks (top-down, bottom-up, comparable company, analogous market). Triangulates across frameworks, highlights where they converge and diverge as signal, and produces a calibrated range with source-graded confidence labels. Refuses unbounded fabrications; always offers a labeled lower-confidence path when data is thin. Used for investment cases, go/no-go decisions, and stakeholder pitches.

How do I install it?

Run `npx skills add product-on-purpose/pm-skills --skill discover-market-sizing --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From product-on-purpose/pm-skills, a repository with 518 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going