Agent SkillsKunAgent/Kun › scientific-problem-selection

scientific-problem-selection

GitHub

评估和优先排序研究问题,基于重要性、新颖性、可行性、证据、资源、伦理和可证伪性。通过工具路由检索文献并评分,辅助科研选题决策。

resources/bundled-skills/scientific-problem-selection/SKILL.md KunAgent/Kun

Trigger Scenarios

需要评估研究问题的优先级 进行科研选题决策 比较候选研究问题

Install

npx skills add KunAgent/Kun --skill scientific-problem-selection -g -y
More Options

Non-standard path

npx skills add https://github.com/KunAgent/Kun/tree/master/resources/bundled-skills/scientific-problem-selection -g -y

Use without installing

npx skills use KunAgent/Kun@scientific-problem-selection

指定 Agent (Claude Code)

npx skills add KunAgent/Kun --skill scientific-problem-selection -a claude-code -g -y

安装 repo 全部 skill

npx skills add KunAgent/Kun --all -g -y

预览 repo 内 skill

npx skills add KunAgent/Kun --list

SKILL.md

Frontmatter
{
    "name": "scientific-problem-selection",
    "description": "Evaluate and prioritize research questions by importance, novelty, tractability, evidence, resources, ethics, and falsifiability."
}

Scientific 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

  1. Define field, decision horizon, available methods, resources, and constraints.
  2. Express each candidate as a falsifiable question with a measurable outcome.
  3. Map current evidence, competing explanations, and decisive experiments.
  4. Score importance, novelty, tractability, risk, ethics, and learning value.
  5. 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.

Version History

  • a984912 Current 2026-09-09 01:50

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Metadata

Files
0
Version
a984912
Hash
22514821
Indexed
2026-09-09 01:50

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