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- Scientific Problem Selection
scientific-problem-selection_skill
- Python
- Official
7.4k
GitHub Stars
2
Bundled Files
3 weeks ago
Catalog Refreshed
2 months ago
First Indexed
Readme & install
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Installation
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npx veilstart add skill anthropics/knowledge-work-plugins --skill scientific-problem-selection- LICENSE.txt10.0 KB
- SKILL.md10.9 KB
Overview
This skill helps scientists choose, evaluate, and rescue research projects using a structured, conversational framework. It guides users through pitching new ideas, troubleshooting stalled work, and navigating strategic decisions so they spend more time on high-impact problems. The approach emphasizes measurable outcomes, honest risk assessment, and practical decision trees.
How this skill works
The skill offers three entry points: pitch a new idea, describe a current problem, or ask a strategic question. For each entry it summarizes the user’s input, asks targeted follow-ups, and applies modular tools — intuition pumps, risk assessment, optimization function, parameter strategy, decision-tree navigation, adversity planning, and problem inversion — to produce concrete next steps. Outputs are short, actionable documents (ideation notes, risk matrices, decision maps) and suggested workarounds.
When to use it
- You have a nascent project idea and want to vet it quickly
- Your experiment or project is stuck and needs troubleshooting
- You must choose between competing research directions
- You need a structured risk assessment before a grant or fellowship
- You want a decision tree to plan go/no-go points
- You need communication-ready summaries for mentors or funders
Best practices
- Start with a 1–2 sentence summary to focus the conversation
- Quantify a single success metric (optimization function) before detailed planning
- Fix one meaningful parameter; let others float to avoid brittleness
- Make a short risk matrix listing assumptions and mitigation steps
- Plan decision points with clear go/no-go criteria and timeframes
- Treat crises as opportunities: fix the issue and upgrade the project concurrently
Example use cases
- Refine a thesis project idea into a 1–2 page ideation document
- Diagnose why an experiment keeps failing and get prioritized fixes and workarounds
- Compare two potential projects by plotting impact vs. feasibility and recommending one
- Create a decision tree for a multi-phase grant with defined milestones and exit rules
- Prepare a concise risk assessment and communication package for a fellowship application
FAQ
Initial conversational triage takes 15–30 minutes; producing short actionable documents typically takes days to a week depending on depth requested.
Will this replace domain-specific expert review?
No. This skill structures problem choice and strategy; it complements domain review and literature validation rather than replacing expert critique.