SKILL FILE

Assumption Audit with AI

List your riskiest assumptions and design fast tests for each one before you build. Stops you from spending 3 months on a feature that depends on something untrue.

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What this skill file teaches Claude

Drop one markdown file into your repo. Claude Code learns how to run this entire workflow.

1

Assumption extraction

Combs through your brief or PRD and surfaces every belief baked into it. Aims for 15-20 assumptions per audit.

2

Risk scoring

Each assumption scored on likelihood it's wrong (1-5) x severity if wrong (1-5). Tagged as desirability, viability, feasibility, or ethical.

3

Cheapest test design

For each high-risk assumption, the cheapest experiment that would credibly disprove it. Hierarchy from desk research to fake-door to concierge MVP.

4

Kill criteria

Specific numeric thresholds ("below 1.5% conversion", "fewer than 3 of 6 interviews") so test results produce decisions, not data.

5

Test order and decision tree

Sequenced test plan with branching logic — what to do if each test passes, fails, or is ambiguous.

6

Cost and timeline per test

Days and dollars for every proposed test so you can budget the validation sprint.

What you can build with this

Pre-build risk reduction

Before engineering starts, audit the brief and test the top 3 risks. A week of validation saves a quarter of building.

Pre-mortem for a new product

Imagine the launch failed. What was the false assumption? Audit lists them and tests the ones that matter.

Defend the roadmap to leadership

Walk into the meeting with risks named, scored, and paired with tests. Replaces hope with a validation plan.

Pivot decision support

Current direction isn't working. Audit reveals which assumption broke, which lets you pivot toward a specific new bet instead of flailing.

Get the full skill file

Everything above is 80% of the skill file. Download the complete version with full implementation details, agent prompts, and ready-to-run scripts.

Common questions

An assumption is something you're treating as true without evidence. A hypothesis is an assumption you've made testable. The audit converts assumptions into hypotheses by adding a kill criterion. "Users will pay $200/mo" is an assumption. "At least 2% of fake-door visitors will click sign up at $200/mo" is a hypothesis. The audit forces every risky assumption to become a hypothesis.
Test everything with a risk score above 9 (likelihood x severity). That's usually 3 to 6 assumptions out of a list of 15 to 20. The rest are either low-risk (test if budget allows, otherwise log them) or already validated by prior work. Testing every assumption is paralysis. Testing none is recklessness. The audit picks the middle path.
Most teams under-imagine. There's almost always a cheaper test than building. Five interviews instead of a prototype. A landing page instead of a beta. A spreadsheet manually run for 5 customers instead of a real product. The audit walks the test hierarchy from cheapest to most expensive and stops at the first one that would credibly disprove the assumption.
Mostly yes, with structure. Lean startup says "test your assumptions" but rarely tells you which ones, in what order, or with what test. The audit forces the inventory, the risk scoring, and the kill criteria. It's the operational layer that turns the Lean Startup mindset into a sprint plan.
Two responses. One: the test was wrong, redesign it (sample too small, criteria too loose, wrong audience). Two: the assumption was less binary than you thought, split it into sub-assumptions and test those. Ambiguous data usually means the kill criterion wasn't specific enough. The audit forces specific kill criteria up front to minimise this.
Especially if you have a PRD. A polished PRD often hides assumptions inside confident-sounding requirements. "Users will complete onboarding in under 5 minutes" reads as a requirement but is actually an assumption that needs testing. The audit is the safety check between PRD approval and engineering kickoff.

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