hypothesis-tree

Structure complex questions into a MECE tree of testable hypotheses.

5|Updated Oct 17, 2011
One-click install
npx skills add https://github.com/klen/dotfiles --skill hypothesis-tree-klen
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: hypothesis-tree
Source: https://github.com/klen/dotfiles/tree/main/.config/opencode/skills/hypothesis-tree
Command: npx skills add https://github.com/klen/dotfiles --skill hypothesis-tree-klen

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you break down complex, ambiguous questions or problems into a structured, hierarchical tree of smaller, testable hypotheses, ensuring all potential angles are considered.

Core Features & Use Cases

  • Structured Decomposition: Organizes complex issues into a MECE (Mutually Exclusive, Collectively Exhaustive) framework.
  • Hypothesis Generation: Guides the creation of specific, testable, and falsifiable hypotheses.
  • Prioritization: Facilitates the prioritization of hypotheses for testing based on evidence, effort, and impact.
  • Use Case: When a product manager sees declining user engagement, they can use this Skill to systematically explore potential reasons, from technical bugs to market shifts, and plan experiments to validate each.

Quick Start

Use the hypothesis-tree skill to break down the question "Why is our user retention dropping?" into a structured tree of hypotheses.

Frequently Asked Questions about hypothesis-tree

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I decompose complex problems into testable hypotheses?

Decomposing complex problems into testable hypotheses involves structuring a central question into a hierarchical tree using the MECE principle, generating first-level hypotheses, and breaking them into sub-hypotheses for systematic investigation.

What is the MECE principle for strategic problem solving?

The MECE principle for strategic problem solving ensures hypotheses are Mutually Exclusive and Collectively Exhaustive, organizing complex issues so all potential angles are considered without overlap, enabling comprehensive decomposition of ambiguous challenges.

How do I structure a hypothesis tree for product validation?

Structuring a hypothesis tree for product validation requires defining a central question like dropping user retention, generating first-level hypotheses, decomposing them into testable sub-hypotheses, and prioritizing each for investigation based on evidence and impact.

When do I need a hypothesis tree for decision making?

You need a hypothesis tree for decision making when facing complex, ambiguous challenges like declining user engagement, requiring systematic exploration of potential reasons from technical bugs to market shifts to plan targeted validation experiments.

What's the best way to prioritize hypotheses for testing?

Prioritizing hypotheses for testing is done by evaluating each generated sub-hypothesis within the decomposition tree based on available evidence, testing effort, and potential impact to determine the optimal investigation sequence.