Scientific Problem Selection

anthropics/knowledge-work-pluginsOfficial

This is a conversational framework for scientists to think through research problem selection, based on Fischbach & Walsh's work in Cell. 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 evaluating feasibility, defining what success looks like, deciding which parameters to fix versus leave flexible, and planning decision points. The core insight is that scientists typically spend days choosing problems and years solving them, which is backwards given that problem choice matters more than execution quality. It's designed to help you invest more upfront time in choosing wisely, with modules for risk assessment, adversity planning, and navigating around obstacles when things inevitably go sideways.

skills.sh installs: 2.5K
GitHub stars: 35.3K
last updated: Aug 21, 2026

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Install

$ npx -y skills add anthropics/knowledge-work-plugins --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