Structure complex questions into MECE testable hypotheses for analysis.
npx skills add https://github.com/Aveer/skills --skill hypothesis-tree-aveer
Please help me install this Agent Skill. Skill: hypothesis-tree Source: https://github.com/Aveer/skills/tree/main/skills/hypothesis-tree Command: npx skills add https://github.com/Aveer/skills --skill hypothesis-tree-aveer
High-intent search queries and answers about installing and using this skill.
Start by framing a specific measurable question, then brainstorm first-level hypotheses organized by MECE categories. Decompose each branch until hypotheses are directly testable, usually within three levels, then prioritize by impact and effort.
MECE means Mutually Exclusive, Collectively Exhaustive: branches must not overlap and together must cover all possibilities. For example, splitting users into new and returning is MECE, while mobile and new users overlap.
Score each hypothesis on available evidence, test effort, and impact if true. Prioritize hypotheses with high impact, low testing effort, and little existing evidence, then record them in a testing plan table.
Use a hypothesis tree when a problem has multiple possible explanations requiring broad MECE coverage. Use Five Whys to drill deep into a single confirmed hypothesis; the two methods combine well.
A strong hypothesis is specific, measurable, and has clear failure criteria, such as "checkout abandonment is above 70% on mobile." Vague statements like "users don't like it" cannot be proven or disproven.
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