← ClaudeAtlas

assumption-mapperlisted

Discovery-stage skill: breaks a product idea into its load-bearing assumptions, ranked riskiest-first, each tagged testable/untestable with a proposed test. Use when the user pitches an idea and asks what it depends on — 'map the assumptions', 'what are we betting on', 'what could kill this', 'what needs to be true', 'riskiest assumption first' — or when /pm routes such a request here. Do NOT use to write the PRD or spec (Build stage), to size the market (opportunity-sizer's job), for knowledge questions about assumption-testing methods, or for analyzing non-product documents.
Abhillashjadhav/PM-agent-OS · ★ 1 · Testing & QA · score 60
Install: claude install-skill Abhillashjadhav/PM-agent-OS
# Assumption Mapper An idea in, its bets out — every bet ranked by risk and paired with the test that would settle it. ## Verification gates (defined first; output is blocked until all pass) - **G1 — Tag completeness:** every assumption carries a `testable` or `untestable` tag. Every `testable` one carries a concrete proposed test (method + the evidence that would confirm or kill it). Every `untestable` one carries why it can't be pre-tested plus either a testable reformulation or an explicit "monitor in market, cannot pre-test" call. A bare tag = gate failure. - **G2 — Ranking is derived:** risk rank follows stated impact × uncertainty, not listing order or vibes. Both factors appear with a one-line basis each. - **G3 — No imported evidence:** the map contains no claims of existing user evidence ("users have told us…", uncited stats). Evidence gathering is the tests' job, not the map's. ## Steps 1. **Restate the idea** in one sentence and confirm the wedge: who, what change, why paid/used. Missing pieces are themselves assumptions — surface, don't fill. 2. **Extract assumptions across the four classic risks:** desirability (they want it), viability (they'll pay / it's worth building), feasibility (we can build it well enough), and adoption/trust (they'll actually switch, integrate, or share data). Aim for the load-bearing 5–9, not an exhaustive 30. 3. **Score each:** impact-if-wrong (H/M/L — what breaks if this is false) and confidence (H/M/L — what we actually know tod