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".
Guides scientists through research problem selection, project ideation, and strategic troubleshooting using structured frameworks.
/plugin marketplace add fergupa/claude_plugins/plugin install bio-research@knowledge-work-pluginsThis skill inherits all available tools. When active, it can use any tool Claude has access to.
LICENSE.txtreferences/01-intuition-pumps.mdreferences/02-risk-assessment.mdreferences/03-optimization-function.mdreferences/04-parameter-strategy.mdreferences/05-decision-tree.mdreferences/06-adversity-planning.mdreferences/07-problem-inversion.mdreferences/08-integration-synthesis.mdreferences/09-meta-framework.mdA conversational framework for systematic scientific problem selection based on Fischbach & Walsh's "Problem choice and decision trees in science and engineering" (Cell, 2024).
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.
Ask: "Tell me the short version of your idea (1-2 sentences)."
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.
Then ask for more detail: "Now give me a bit more detail. You might include, however briefly or even say where you are unsure:
From there, guide the user through the early stages of problem selection and evaluation:
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.
Ask: "Tell me a short version of your problem (1-2 sentences or whatever is easy)."
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.
Then ask: "Now give me a bit more detail. You might include, however briefly:
From there, guide the user through troubleshooting and decision tree navigation:
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.
Ask: "Tell me the short version of your question (1-2 sentences)."
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.
Then ask: "Now give me a bit more detail. You might include, however briefly:
From there, draw on the specific modules from the problem choice framework most appropriate to the question:
See the complete reference materials in the references/ folder.
Problem Choice >> Execution Quality
Even brilliant execution of a mediocre problem yields incremental impact. Good execution of an important problem yields substantial impact.
Scientists typically spend:
This imbalance limits impact. These skills help invest more time choosing wisely.
For Evaluating Ideas:
Skills help move ideas rightward (more feasible) and upward (more impactful).
| 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 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)
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 |
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.
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