scientific-problem-selection
Evaluate and prioritize research questions by importance, novelty, tractability, evidence, resources, ethics, and falsifiability.
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tessl review fix ./resources/bundled-skills/scientific-problem-selection/SKILL.mdScientific Problem Selection
Copyright (c) 2026 KunAgent. Licensed under the MIT License.
Purpose
Evaluate and prioritize research questions by importance, novelty, tractability, evidence, resources, ethics, and falsifiability.
Tool routing
| Tool or skill | Use |
|---|---|
web_fetch | Retrieve public papers, datasets, calls, or standards. |
browser_use | Inspect public literature and research portals. |
render_chart | Compare candidate problems using structured criteria. |
load_skill | Load the scholarly-research skill for a dedicated literature review. |
Workflow
- Define field, decision horizon, available methods, resources, and constraints.
- Express each candidate as a falsifiable question with a measurable outcome.
- Map current evidence, competing explanations, and decisive experiments.
- Score importance, novelty, tractability, risk, ethics, and learning value.
- Choose a portfolio with a lead problem and fallback path.
Completion gates
- Verify novelty claims against current literature.
- Identify required sample size, data access, and ethical approvals.
- State what result would change the research direction.
Boundaries
- Do not equate fashionable topics with important questions.
- Do not recommend work that lacks a plausible ethical and resource path.
Delivery
Lead with the outcome, name the evidence used for verification, and disclose any real limitation that remains.
- Repository
KunAgent/Kun
- Revision
8e16760
- Last updated
- First committed
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