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Scientific Problem Selection

AnthropicOfficialPublished by Anthropic

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From the author

This skill should be used when scientists need help with research problem selection, project ideation, troubleshooting stuck projects, or strategic scientific decisions. Use this skill when users ask to pitch a new research idea, work through a project problem, evaluate project risks, plan research strategy, navigate decision trees, or get help choosing what scientific problem to work on. Typical requests include "I have an idea for a project", "I'm stuck on my research", "help me evaluate this project", "what should I work on", or "I need strategic advice about my research".
— the description by Anthropic

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

Scientific Problem Selection provides a structured, conversational approach to navigating the research lifecycle. Based on the principles of problem choice over execution quality, this skill helps researchers move from initial ideation to strategic planning. It guides users through nine specific modules—including intuition pumps, risk assessment, and decision tree navigation—to ensure that time is invested in high-impact, feasible problems. By treating research as a series of testable assumptions and strategic decision points, the framework helps scientists avoid common pitfalls, manage adversity, and optimize their research strategy.

What it does

  • Facilitates project ideation using structured intuition pumps.
  • Performs rigorous risk assessment and assumption analysis.
  • Defines success metrics through optimization functions.
  • Navigates complex decision trees for project troubleshooting.
  • Provides strategies for adversity response and problem inversion.
  • Synthesizes research plans into coherent communication packages.

When to use it

  • When choosing a new thesis, postdoc, or lab research direction.
  • When a project is stuck and requires a strategic pivot.
  • When evaluating the feasibility and impact of a new research idea.
  • When planning long-term research strategy or navigating career transitions.
  • When preparing for committee meetings or grant applications.

Advantages

  • Increases research impact by prioritizing problem selection over incremental execution.
  • Reduces time wasted on dead-end projects through early risk identification.
  • Provides a repeatable, evidence-based framework for scientific decision-making.
  • Helps transform crises into opportunities for project growth.
  • Encourages objective evaluation of biological and technical assumptions.

Usage examples

“I have an idea for a new project involving CRISPR, but I am not sure if it is worth pursuing.”
The agent initiates the ideation workflow, asking for a summary and guiding the user through intuition pumps to refine the idea and assess its potential impact.
“My current experiment is failing and I am stuck. Can you help me troubleshoot?”
The agent shifts to the troubleshooting workflow, helping the user identify the core problem, analyze assumptions, and navigate the decision tree to find a path forward.
“I need to evaluate the risks of my proposed research strategy.”
The agent leads the user through a systematic risk assessment, helping to list assumptions, score them by risk level and time-to-test, and identify potential red flags.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/anthropics/scientific-problem-selection/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip scientific-problem-selection.zip -d .agents/skills

Documentation by Anthropic

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.

Files

references/07-problem-inversion.md

SKILL 7: Problem Inversion Strategies ("Turn It On Its Head")

Overview

This skill provides three concrete strategies for navigating around obstacles by reframing problems. When stuck, instead of pushing harder on the current approach, try inverting the problem.

Core Principle

"Turn a problem on its head"

Three powerful strategies:

  1. Unfix parameters (covered in Skill 4, applied here in crisis)

  2. Don't achieve goal A? Achieve comparable goal B

  3. "I have the answer; what is the question?"

Strategy 1: Unfix Parameters (In Crisis Mode)

When to Use: Run-of-the-mill issues in project execution

Approach: Let a "sacred" fixed parameter float

Example from Lecture:

  • Stuck: Spatial transcriptomics of APC-T cell interactions in tumor microenvironment

  • All fixed: Technique, cell types, context

  • Inversion:

    • Unfix technique → What else could measure these interactions?

    • Unfix cell types → What other interactions matter in tumors?

    • Unfix context → Where else do APC-T interactions matter?

Your Application: For each fixed parameter in your project:

  • What if this floated?

  • What alternatives exist?

  • Which would be easier/faster/more informative?

Strategy 2: Comparable Goal Substitution

When to Use: Existential threats to project (can't achieve original goal)

Approach: Achieve a different but equally valuable goal

Mindset Shift:

  • Wrong: "I failed to do X"

  • Right: "The world needs Y instead, which I CAN do"

Example from Lectures: PROTAC Story

  • Goal A (Failed): Degrade specific therapeutic target

  • Goal B (Achieved): Map which kinases ARE degradable

  • Value: B is more impactful (general principle + method validation)

  • Learning: Target engagement ≠ degradation (important discovery)

Framework:

  1. Original goal: [What you wanted]

  2. Why it failed: [Specific reason]

  3. What CAN you do with current data/tools: [Capabilities]

  4. Comparable goals:

    • Option 1: [Different but related goal]

    • Option 2: [Another alternative]

    • Option 3: [Yet another]

  5. Which is most valuable: [Analysis]

  6. How to frame it: [Communication strategy]

Strategy 3: Answer Seeking Question

When to Use: End-of-project challenges (interpretation, framing, application)

Approach: You got an answer, but not to your original question. What question DOES your data answer?

Mindset Shift:

  • Wrong: "This doesn't answer my question"

  • Right: "What interesting question does this answer?"

Example from Lectures: Steroid Receptor

  • Original Question: What is THE receptor for this steroid?

  • Answer Obtained: Binds multiple receptors at different affinities

  • Problem: Can't answer original question (no single receptor)

  • Inversion: "What question does this answer?"

  • New Question: How does finite receptor pool sense infinite lipids?

  • Answer: Combinatorial sensing (pattern = unique "chord")

  • Impact: More interesting than intended finding

Framework:

  1. Original question: [What you asked]

  2. Data obtained: [What you actually found]

  3. Why it doesn't answer: [The mismatch]

  4. What DOES the data show clearly: [Solid findings]

  5. What questions could these answer:

    • Question 1: [Option]

    • Question 2: [Option]

    • Question 3: [Option]

  6. Which is most interesting: [Assessment]

  7. How to reframe paper/project: [New framing]

Workflow

Phase 1: Identify Your Obstacle
  • Type: Technical / Biological / Competitive / Interpretive

  • Severity: Run-of-mill / Existential / End-stage

  • Description: [What's blocking you]

Phase 2: Select Strategy
Obstacle TypeRecommended Strategy
Technical barrier, mid-projectStrategy 1 (Unfix parameters)
Can't achieve original goalStrategy 2 (Comparable goal)
Have data, unclear what it meansStrategy 3 (Answer seeking question)
Phase 3: Apply Strategy

Work through the relevant framework above with your specific situation.

Phase 4: Evaluate Alternatives

For each alternative generated:

  • Scientific value: How interesting is this?

  • Feasibility: How hard to execute?

  • Timeline: How long will it take?

  • Impact: How does this compare to original plan?

  • Your advantage: Do you still have edge here?

Output: Problem Inversion Analysis

Page 1: Current Situation

  • Obstacle: [Clear description]

  • Why you're stuck: [Root cause]

  • Original plan: [What you intended]

  • Current capability: [What you CAN do]

Page 2: Strategy Applications

Strategy 1 (Unfix Parameters):

Fixed ParameterIf This FloatedAlternative ApproachesAssessment
[Param 1][Consequences][Options][Value]

Strategy 2 (Comparable Goals):

Original GoalWhy It FailedComparable GoalValue Assessment
[Goal A][Reason][Goal B][Compare impact]

Strategy 3 (Answer → Question):

  • Data obtained: [What you have]

  • Question 1 it could answer: [Option 1]

  • Question 2 it could answer: [Option 2]

  • Question 3 it could answer: [Option 3]

  • Most interesting: [Selection + reasoning]

Page 3: Recommended Path

  • Selected strategy: [1, 2, or 3]

  • New direction: [Specific plan]

  • Why this is better: [Not just "it works" but "it's more interesting"]

  • Communication approach: [How to frame this pivot]

  • Timeline: [New schedule]

Requirements and compatibility

Written for: Claude Code, Claude apps

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

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Attribution and licence

Published by
Anthropic
Publisher
Anthropic (Official)
Source
anthropics/knowledge-work-plugins · bio-research/skills/scientific-problem-selection · commit e050c2e
Licence
Apache License 2.0 (redistribution allowed)
  • ATTRIBUTION.md (written by AutoGineer)
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