scientific-problem-selection by anthropics/knowledge-work-plugins
npx skills add https://github.com/anthropics/knowledge-work-plugins --skill scientific-problem-selection基于 Fischbach & Walsh 的《科学与工程中的问题选择与决策树》(Cell,2024 年)的系统性科学问题选择对话框架。
为用户提供三个切入点:
1) 提出一个新项目的想法 —— 共同完善它
2) 分享当前项目中的一个问题 —— 共同排查故障
3) 提出一个战略性问题 —— 共同导航决策树
这种对话切入点从科学家当前所处的位置出发,并建立协作基调。
询问:"请用简短版本告诉我你的想法(1-2 句话)。"
用户分享想法后,返回一个快速摘要(不超过一段),展示理解。注意研究的大致领域,并以突出其核心的方式重新表述想法——表明已理解并准备好深入细节。
然后询问更多细节:"现在请给我更多细节。你可以包括,无论多么简短,甚至可以说出你不确定的地方:
从那里开始,引导用户完成问题选择和评估的早期阶段:
详细指南请参阅 references/01-intuition-pumps.md、、 和 。
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references/02-risk-assessment.mdreferences/03-optimization-function.mdreferences/04-parameter-strategy.md询问:"请用简短版本告诉我你的问题(1-2 句话或任何容易说的)。"
用户分享问题后,返回一个快速摘要(不超过一段),展示理解。注意问题发生的项目背景,并重新表述问题——突出其核心本质——以便用户知道情况已被理解。同时提出其他似乎重要的讨论问题。
然后询问:"现在请给我更多细节。你可以包括,无论多么简短:
从那里开始,引导用户进行故障排除和决策树导航:
无论问题是否容易解决,始终包含可能有用的变通方法。
详细指南请参阅 references/05-decision-tree.md、references/06-adversity-planning.md、references/07-problem-inversion.md 和 references/04-parameter-strategy.md。
询问:"请用简短版本告诉我你的问题(1-2 句话)。"
用户分享问题后,返回一个快速摘要(不超过一段),展示理解。注意更广泛的背景,并重新表述问题——突出其症结——以确认与他们的想法一致。
然后询问:"现在请给我更多细节。你可以包括,无论多么简短:
从那里开始,根据问题选择框架中最适合该问题的特定模块:
请参阅 references/ 文件夹中的完整参考资料。
问题选择 >> 执行质量
即使平庸问题的出色执行也只能产生渐进式影响。重要问题的良好执行则能产生实质性影响。
科学家通常花费:
这种不平衡限制了影响力。这些技能有助于投入更多时间明智地选择。
用于评估想法:
技能帮助想法向右移动(更可行)和向上移动(更有影响力)。
| 技能 | 目的 | 输出 | 时间 |
|---|---|---|---|
| 1. 直觉泵 | 生成高质量的研究想法 | 问题构思文档 | ~1 周 |
| 2. 风险评估 | 识别和管理项目风险 | 风险评估矩阵 | 3-5 天 |
| 3. 优化函数 | 定义成功指标 | 影响力评估文档 | 2-3 天 |
| 4. 参数策略 | 决定固定什么与保持灵活 | 参数策略文档 | 2-3 天 |
| 5. 决策树导航 | 规划决策点和高度切换 | 决策树地图 | 2 天 |
| 6. 逆境响应 | 为危机作为机会做准备 | 逆境应对手册 | 2 天 |
| 7. 问题反转 | 绕过障碍 | 问题反转分析 | 1 天 |
| 8. 整合与综合 | 综合成连贯的计划 | 项目沟通包 | 3-5 天 |
| 9. 元框架 | 编排完整的工作流程 | 完整的项目包 | 1-6 周 |
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)
详细的技能文档可在 references/ 文件夹中找到:
| 文件 | 内容 | 搜索模式 |
|---|---|---|
01-intuition-pumps.md | 生成研究想法 | Intuition Pump #, Trap #, Phase [0-9] |
02-risk-assessment.md | 风险识别 | Risk.*1-5, go/no-go, assumption |
03-optimization-function.md | 成功指标 | Generality.*Learning, optimization, impact |
04-parameter-strategy.md | 参数固定 | fixed.*float, constraint, parameter |
05-decision-tree.md | 决策树导航 | altitude, Level [0-9], decision |
06-adversity-planning.md | 逆境响应 | adversity, crisis, ensemble |
07-problem-inversion.md | 问题反转策略 | Strategy [0-9], inversion, goal |
08-integration-synthesis.md | 整合与综合 | narrative, communication, story |
09-meta-framework.md | 完整工作流程 | Phase, workflow, orchestrat |
Fischbach, M.A., & Walsh, C.T. (2024). "Problem choice and decision trees in science and engineering." Cell , 187, 1828-1833.
基于斯坦福大学讲授的课程 BIOE 395。
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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.
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 |
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 |
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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10,500 周安装
| 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 |
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 |