scientific-problem-selection
A collaborative framework for scientists to evaluate ideas, troubleshoot research, and plan strategies.
Install
mkdir -p .claude/skills/scientific-problem-selection && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/1925" && unzip -o skill.zip -d .claude/skills/scientific-problem-selection && rm skill.zipInstalls to .claude/skills/scientific-problem-selection
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
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".Key capabilities
- →Pitches research ideas via structured ideation
- →Troubleshoots stalled experimental projects
- →Navigates complex strategic decision trees
- →Evaluates project-specific risk profiles
How it works
Applies a conversational framework based on established scientific decision trees to guide users through iterative hypothesis testing and risk assessment.
Inputs & outputs
When to use scientific-problem-selection
- →Pitching a new scientific research idea
- →Troubleshooting a stuck experiment
- →Evaluating project risks
- →Navigating scientific strategic decision trees
About this skill
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:
- What exactly you want to do
- How you currently plan to do it
- If it works, why will it be a big deal
- 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:
- The overall goal of your project (if we have not talked about it before)
- What exactly went wrong
- 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:
- The setting (i.e., is this about a current or future project)
- 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
| Skill | Purpose | Output | Time |
|---|---|---|---|
| 1. Intuition Pumps | Generate high-quality research ideas | Problem Ideation Document | ~1 week |
| 2. Risk Assessment | Identify and manage project risks | Risk Assessment Matrix | 3-5 days |
| 3. Optimization Function | Define success metrics | Impact Assessment Document | 2-3 days |
| 4. Parameter Strategy | Decide what to fix vs. keep flexible | Parameter Strategy Document | 2-3 days |
| 5. Decision Tree Navigation | Plan decision points and altitude dance | Decision Tree Map | 2 days |
| 6. Adversity Response | Prepare for crises as opportunities | Adversity Playbook | 2 days |
| 7. Problem Inversion | Navigate around obstacles | Problem Inversion Analysis | 1 day |
| 8. Integration & Synthesis | Synthesize into coherent plan | Project Communication Package | 3-5 days |
| 9. Meta-Framework | Orchestrate complete workflow | Complete Project Package | 1-6 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
- Conversational Entry - Meet users where they are with three clear starting points
- Thoughtful Interaction - Ask clarifying questions; low confidence prompts additional input
- Literature Integration - Use PubMed searches at strategic points for validation
- Concrete Outputs - Every skill produces tangible 1-2 page documents
- Building Specificity - Progressive detail emerges through targeted questions
- Flexibility - Skills work independently, sequentially, or iteratively
- 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:
| File | Content | Search Patterns |
|---|---|---|
01-intuition-pumps.md | Generate research ideas | Intuition Pump #, Trap #, Phase [0-9] |
02-risk-assessment.md | Risk identification | Risk.*1-5, go/no-go, assumption |
03-optimization-function.md | Success metrics | Generality.*Learning, optimization, impact |
04-parameter-strategy.md | Parameter fixation | fixed.*float, constraint, parameter |
05-decision-tree.md | Decision tree navigation | altitude, Level [0-9], decision |
06-adversity-planning.md | Adversity response | adversity, crisis, ensemble |
07-problem-inversion.md | Problem inversion strategies | Strategy [0-9], inversion, goal |
08-integration-synthesis.md | Integration and synthesis | narrative, communication, story |
09-meta-framework.md | Complete workflow | Phase, workflow, orchestrat |
Expected Outcomes
Immediate (After Completing Workflow)
- Clear project vision
- Honest risk assessment
- Contingency plans
- Communication materials rea
Content truncated.
When not to use it
- →Performing primary literature searches or database lookups
- →Writing actual code or executing laboratory experiments
Limitations
- →Limited by the user's initial project clarity
- →Cannot generate empirical experimental data
- →Dependent on researcher domain expertise for validation
How it compares
Provides a systematic logical framework for research strategy rather than generic project management advice.
Compared to similar skills
scientific-problem-selection side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| scientific-problem-selection (this skill) | 20 | 6mo | No flags | Intermediate |
| literature-review | 559 | 2mo | Review | Advanced |
| openalex-database | 48 | 7mo | Review | Intermediate |
| market-research-reports | 38 | 7mo | Review | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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