Discover Market Sizing
Estimate market opportunity (TAM, SAM, SOM) using multiple sizing frameworks (top-down...
Install
npx skills add product-on-purpose/pm-skills --skill discover-market-sizing -g -a claude-code -y- Repository
- product-on-purpose/pm-skills780
- Category
- Engineering
- Updated
- 5d ago
- License
- Apache-2.0
- Context cost
- Mediumabout 3,000 tokens
- Runs scripts
- No, instructions only
What it does
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.
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 reasoning, or (c) a sensitivity range showing the bounds. Hand-wavy guesses are a P0 anti-pattern. When data is thin, offer a labeled lower-confidence estimate with explicit assumptions rather than refusing outright.
Scope: external market opportunity only. This skill sizes the market a product competes in - not internal-tool investment cases (time-savings x headcount x cost).
