Scientific Problem Selection

This is a structured framework for helping scientists choose better research problems, based on Fischbach & Walsh's decision tree methodology. It gives you three entry points: pitch a new idea, troubleshoot a stuck project, or ask a strategic question. From there it walks you through nine specific skills like intuition pumps, risk assessment, and parameter strategy. The core insight is that scientists typically spend days choosing problems and years solving them, which is backwards. What I like here is the conversational scaffolding. It doesn't dump theory on you, it asks for a short version first, reflects it back, then goes deeper. Useful if you're actually doing research and need to think through project selection systematically rather than just following your gut.

skills.sh installs: 267
GitHub stars: 645
last updated: Aug 21, 2026

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Install

$ npx -y skills add anthropics/life-sciences --skill scientific-problem-selection --agent claude-code

Installs into .claude/skills of the current project.

Files

Scientific Problem Selection Skills

A conversational framework for systematic scientific problem selection based on Fischbach & Walsh's "Problem choice and decision trees in science and engineering" (Cell, 2024).

Getting Started

Present users with three entry points:

1) Pitch an idea for a new project — to work it up together

2) Share a problem in a current project — to troubleshoot together

3) Ask a strategic question — to navigate the decision tree together

This conversational entry meets scientists where they are and establishes a collaborative tone.

Option 1: Pitch an Idea

Initial Prompt

Ask: "Tell me the short version of your idea (1-2 sentences)."

Response Approach

After the user shares their idea, return a quick summary (no more than one paragraph) demonstrating understanding. Note the general area of research and rephrase the idea in a way that highlights its kernel—showing alignment and readiness to dive into details.

SKILL.md on GitHub