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Scientific Problem Selection

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Streamline your research problem selection process.

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What Scientific Problem Selection does

The Scientific Problem Selection skill provides a structured approach for scientists to identify and evaluate research problems effectively. It is designed to assist users in pitching new project ideas, troubleshooting existing challenges, and making strategic decisions regarding their research direction. This skill is grounded in the principles outlined in Fischbach & Walsh's work on decision trees in science and engineering, ensuring a rigorous and systematic methodology.

Users can initiate their interaction through three main entry points: pitching an idea, sharing a project problem, or asking a strategic question. Each entry point is crafted to foster a collaborative environment, allowing users to articulate their thoughts clearly while receiving constructive feedback. The skill encourages a detailed exploration of the user's ideas or problems, guiding them through a series of thoughtful prompts that help refine their concepts and assess potential risks.

The workflow encompasses various skills that address different aspects of problem selection and project management. For instance, users can utilize intuition pumps to generate high-quality research ideas, conduct risk assessments to identify project vulnerabilities, and apply optimization functions to define success metrics. This comprehensive approach ensures that users not only select viable problems but also enhance their overall research strategy.

Designed primarily for graduate students, postdocs, principal investigators, and startup founders, this skill is ideal for anyone involved in scientific research who seeks to improve their decision-making process. By investing time in problem selection, users can maximize the impact of their research efforts, ultimately leading to more significant contributions to their fields.

When to use it

Use this skill when you need guidance on pitching new research ideas, troubleshooting project issues, or evaluating strategic options in your research.

When not to use it

This skill may not be suitable for users looking for technical solutions or direct coding assistance, as it focuses on problem selection and strategic planning rather than execution.

What you can build with it

Pitching a New Research Idea

A graduate student uses the skill to refine their research proposal by articulating their idea and receiving structured feedback.

Troubleshooting a Stuck Project

A postdoc encounters a significant issue in their current research and utilizes the skill to navigate through the problem and explore solutions.

Evaluating Strategic Research Options

A principal investigator seeks advice on which project to prioritize and uses the skill to assess potential risks and impacts.

How to install Scientific Problem Selection

View source

1. Install with the skills CLI

npx skills add anthropics/knowledge-work-plugins/scientific-problem-selection --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by anthropics

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.

Follow-up Prompt

Then ask for more detail: "Now give me a bit more detail. You might include, however briefly or even say where you are unsure:

  1. What exactly you want to do
  2. How you currently plan to do it
  3. If it works, why will it be a big deal
  4. What you think are the major risks"

Workflow

From there, guide the user through the early stages of problem selection and evaluation:

  • Skill 1: Intuition Pumps - Refine and strengthen the idea
  • Skill 2: Risk Assessment - Identify and manage project risks
  • Skill 3: Optimization Function - Define success metrics
  • Skill 4: Parameter Strategy - Determine what to fix vs. keep flexible

See references/01-intuition-pumps.md, references/02-risk-assessment.md, references/03-optimization-function.md, and references/04-parameter-strategy.md for detailed guidance.


Option 2: Troubleshoot a Problem

Initial Prompt

Ask: "Tell me a short version of your problem (1-2 sentences or whatever is easy)."

Response Approach

After the user shares their problem, return a quick summary (no more than one paragraph) demonstrating understanding. Note the context of the project where the problem occurred and rephrase the problem—highlighting its core essence—so the user knows the situation is understood. Also raise additional questions that seem important to discuss.

Follow-up Prompt

Then ask: "Now give me a bit more detail. You might include, however briefly:

  1. The overall goal of your project (if we have not talked about it before)
  2. What exactly went wrong
  3. Your current ideas for fixing it"

Workflow

From there, guide the user through troubleshooting and decision tree navigation:

  • Skill 5: Decision Tree Navigation - Plan decision points and navigate between execution and strategic thinking
  • Skill 4: Parameter Strategy - Fix one parameter at a time, let others float
  • Skill 6: Adversity Response - Frame problems as opportunities for growth
  • Skill 7: Problem Inversion - Strategies for navigating around obstacles

Always include workarounds that might be useful whether or not the problem can be fixed easily.

See references/05-decision-tree.md, references/06-adversity-planning.md, references/07-problem-inversion.md, and references/04-parameter-strategy.md for detailed guidance.


Option 3: Ask a Strategic Question

Initial Prompt

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

Response Approach

After the user shares their question, return a quick summary (no more than one paragraph) demonstrating understanding. Note the broader context and rephrase the question—highlighting its crux—to confirm alignment with their thinking.

Follow-up Prompt

Then ask: "Now give me a bit more detail. You might include, however briefly:

  1. The setting (i.e., is this about a current or future project)
  2. A bit more detail about what you're thinking"

Workflow

From there, draw on the specific modules from the problem choice framework most appropriate to the question:

  • Skills 1-4 for future project planning (ideation, risk, optimization, parameters)
  • Skills 5-7 for current project navigation (decision trees, adversity, inversion)
  • Skill 8 for communication and synthesis
  • Skill 9 for comprehensive workflow orchestration

See the complete reference materials in the references/ folder.


Core Framework Concepts

The Central Insight

Problem Choice >> Execution Quality

Even brilliant execution of a mediocre problem yields incremental impact. Good execution of an important problem yields substantial impact.

The Time Paradox

Scientists typically spend:

  • Days choosing a problem
  • Years solving it

This imbalance limits impact. These skills help invest more time choosing wisely.

Evaluation Axes

For Evaluating Ideas:

  • X-axis: Likelihood of success
  • Y-axis: Impact if successful

Skills help move ideas rightward (more feasible) and upward (more impactful).

The Risk Paradox

  • Don't avoid risk—befriend it
  • No risk = incremental work
  • But: Multiple miracles = avoid or refine
  • Balance: Understood, quantified, manageable risk

The Parameter Paradox

  • Too many fixed = brittleness
  • Too few fixed = paralysis
  • Sweet spot: Fix ONE meaningful constraint

The Adversity Principle

  • Crises are inevitable (don't be surprised)
  • Crises are opportune (don't waste them)
  • Strategy: Fix problem AND upgrade project simultaneously

The 9 Skills Overview

SkillPurposeOutputTime
1. Intuition PumpsGenerate high-quality research ideasProblem Ideation Document~1 week
2. Risk AssessmentIdentify and manage project risksRisk Assessment Matrix3-5 days
3. Optimization FunctionDefine success metricsImpact Assessment Document2-3 days
4. Parameter StrategyDecide what to fix vs. keep flexibleParameter Strategy Document2-3 days
5. Decision Tree NavigationPlan decision points and altitude danceDecision Tree Map2 days
6. Adversity ResponsePrepare for crises as opportunitiesAdversity Playbook2 days
7. Problem InversionNavigate around obstaclesProblem Inversion Analysis1 day
8. Integration & SynthesisSynthesize into coherent planProject Communication Package3-5 days
9. Meta-FrameworkOrchestrate complete workflowComplete Project Package1-6 weeks

Skill Workflow

SKILL 1: Intuition Pumps
         | (generates idea)
         v
SKILL 2: Risk Assessment
         | (evaluates feasibility)
         v
SKILL 3: Optimization Function
         | (defines success metrics)
         v
SKILL 4: Parameter Strategy
         | (determines flexibility)
         v
SKILL 5: Decision Tree
         | (plans execution and evaluation)
         v
SKILL 6: Adversity Planning
         | (prepares for failure modes)
         v
SKILL 7: Problem Inversion
         | (provides pivot strategies)
         v
SKILL 8: Integration & Communication
         | (synthesizes into coherent plan)
         v
SKILL 9: Meta-Skill
         (orchestrates complete workflow)

Key Design Principles

  1. Conversational Entry - Meet users where they are with three clear starting points
  2. Thoughtful Interaction - Ask clarifying questions; low confidence prompts additional input
  3. Literature Integration - Use PubMed searches at strategic points for validation
  4. Concrete Outputs - Every skill produces tangible 1-2 page documents
  5. Building Specificity - Progressive detail emerges through targeted questions
  6. Flexibility - Skills work independently, sequentially, or iteratively
  7. Scientific Rigor - Claims about generality and feasibility should be evidence-based

Who Should Use These Skills

Graduate Students (Primary Audience)

  • When: Choosing thesis projects, qualifying exams, committee meetings
  • Focus: Skills 1-3 (ideation, risk, impact) + Skill 9 (complete workflow)
  • Timeline: 2-4 weeks for comprehensive planning

Postdocs

  • When: Starting new position, planning independent projects, fellowship applications
  • Focus: All skills, emphasizing independence and risk management
  • Timeline: 1-2 weeks intensive planning

Principal Investigators

  • When: New lab, new direction, mentoring trainees, grant cycles
  • Focus: Skills 1, 3, 4, 6 (ideation, impact, parameters, adversity)
  • Timeline: Ongoing, integrate into lab culture

Startup Founders

  • When: Company inception, pivot decisions, investor pitches
  • Focus: Skills 1-4 (ideation through parameters) + Skill 8 (communication)
  • Timeline: 1-2 weeks for initial planning, revisit quarterly

Reference Materials

Detailed skill documentation is available in the references/ folder:

FileContentSearch Patterns
01-intuition-pumps.mdGenerate research ideasIntuition Pump #, Trap #, Phase [0-9]
02-risk-assessment.mdRisk identificationRisk.*1-5, go/no-go, assumption
03-optimization-function.mdSuccess metricsGenerality.*Learning, optimization, impact
04-parameter-strategy.mdParameter fixationfixed.*float, constraint, parameter
05-decision-tree.mdDecision tree navigationaltitude, Level [0-9], decision
06-adversity-planning.mdAdversity responseadversity, crisis, ensemble
07-problem-inversion.mdProblem inversion strategiesStrategy [0-9], inversion, goal
08-integration-synthesis.mdIntegration and synthesisnarrative, communication, story
09-meta-framework.mdComplete workflowPhase, workflow, orchestrat

Expected Outcomes

Immediate (After Completing Workflow)

  • Clear project vision
  • Honest risk assessment
  • Contingency plans
  • Communication materials ready
  • Confidence in problem choice

6-Month

  • Faster decisions (have framework)
  • Productive adversity handling
  • No existential crises (risks mitigated)

2-Year

  • Published results or strong progress
  • Avoided dead-end projects
  • Career aligned with goals
  • Time well-spent (ultimate measure)

Foundational Reference

Fischbach, M.A., & Walsh, C.T. (2024). "Problem choice and decision trees in science and engineering." Cell, 187, 1828-1833.

Based on course BIOE 395 taught at Stanford University.

Frequently asked questions about Scientific Problem Selection

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