stress-test

Skill: Stress Test

Type: Standalone — reviews any analysis plan for methodological flaws

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Purpose

Takes an analysis plan, investigation design, or analytical approach and pressure-tests it for hidden flaws — wrong baselines, survivorship bias, missing segments, uncontrolled confounds, and absent kill criteria. Acts as a "senior data scientist code review" for your analytical thinking.

This skill is standalone — it works on any analysis plan, whether produced by /analysis-design, written by the user, or pulled from an existing document.

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When to Use

• Before committing a week to executing an analysis plan
• Before presenting an analysis design to stakeholders
• When you've written an analysis brief and want a gut-check
• When reviewing someone else's analytical approach
• After an analysis came back with unexpected results (was the design flawed?)

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Inputs

Input	Required	Source	Description
{{PLAN}}	Yes	User or file path	The analysis plan to review. Can be a file path, pasted text, or a description of the approach
{{CONTEXT}}	No	User	Business context — what decision this analysis will inform
{{AUDIENCE}}	No	User	Who will consume the results (affects what counts as "fatal" vs. "nice to have")
{{DATA_DESCRIPTION}}	No	User	Description of available data, if not obvious from the plan

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The 7-Point Stress Test

Check data availability first. A methodologically perfect plan that needs data the dataset lacks is unexecutable, so this check precedes the seven checkpoints:

1. Read the active dataset schema (.knowledge/datasets/{active}/schema.md)
2. Check if the plan's required fields/tables/dimensions exist in the dataset
3. If ANY required data is missing → HALT, skip checkpoints 1-6, jump straight to checkpoint 7, assign FAIL verdict with BLOCKER status, provide F grade, and stop
4. If all required data exists → proceed with checkpoints 1-7 in order