instrument-data-to-all…
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when…
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
$ npx -y skills add anthropics/knowledge-work-plugins --skill scientific-problem-selection --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/scientific-problem-selectionContext preview
The summary Claude sees to decide when to auto-load this skill.
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
name: scientific-problem-selection description: 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".
A 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.
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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: 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"
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.
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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: 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"
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.
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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: 1. The setting (i.e., is this about a current or future project) 2. A bit more detail about what you're thinking"
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.
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**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).
Plugins that turn Claude into a specialist for your role, team, and company. Built for Claude Cowork, also compatible with Claude Code.
Repo: anthropics/knowledge-work-plugins
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when…
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