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Feynman Cognition — Cognitive Atom Deconstruction Framework

作者 OpenLark · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install feynman-cognition
功能描述
Five-step Feynman framework to deeply understand concepts by plain explanation, consensus mapping, surfacing controversies, cross-disciplinary connections, a...
使用说明 (SKILL.md)

Feynman Cognition — Cognitive Atom Deconstruction Framework

"If you can't explain it simply, you don't understand it well enough." — Richard Feynman

Use Cases

Activate when users need deep understanding of a concept, deconstruction of complex problems, Feynman-style learning, or say "explain it the Feynman way," "Feynman learning method," "make this clear," "help me truly understand," "Feynman it." Also applies to requests like "explain from the ground up," "a different angle," "what are the boundaries of this concept," "how do different disciplines view this." Do not activate for simple definition queries or fact checks — only activate when deep understanding, multi-angle deconstruction, or cross-disciplinary connection is needed.

Activation Criteria

Activate when (any of the following):

  • User explicitly mentions: Feynman, Feynman technique, explain clearly, truly understand, underlying principles
  • User wants deep understanding of a concept, theory, technology, or phenomenon
  • User asks "explain from a different angle," "where are the boundaries," "how do different disciplines view this"
  • User says "help me break this down," "what does this actually mean"

Do NOT activate:

  • Simple definition queries ("what is X" needing only a one-sentence answer)
  • Pure fact confirmation ("what year did X happen")
  • User just wants to quickly look up a piece of data or a name

Workflow

After receiving a question, execute the five steps in order. Each step is the foundation for the next. Do not skip.


Step 1: Plain-Language Explanation (Explain Like I'm 12)

Goal: Explain the concept in the simplest possible language so a 12-year-old can understand.

Rules:

  • No jargon unless you define it first
  • Use analogies — find everyday equivalents
  • If you can't explain it clearly, you don't understand it yet. Go back and relearn
  • Keep it to 3-5 sentences

Self-check: Could my mom understand this? If not, start over.

Output format:

💬 Plain-Language Version: [3-5 simplest sentences, zero jargon]


Step 2: Map the Consensus

Goal: Map out the academic/industry consensus framework for this concept — what does everyone agree on.

Rules:

  • List 3-5 widely accepted consensus points
  • Label confidence level for each (broad consensus / mainstream view / contested)
  • If supported by classic experiments, key papers, or milestone events, briefly mention them
  • Distinguish "facts" from "mainstream interpretations" — they are not the same thing

Output format:

📋 Consensus Map:

  1. [Consensus point 1] — Confidence: broad consensus / Evidence: [key evidence]
  2. [Consensus point 2] — Confidence: mainstream view / Evidence: [key evidence] ...

Step 3: Surface the Controversies

Goal: Identify the real controversies in the field — where are people still arguing, where is consensus starting to crack.

Rules:

  • List 2-4 genuine controversies (not strawmen)
  • For each, present both sides' core arguments
  • Label intensity (intense / moderate / emerging)
  • Honestly note "what we don't know" — this is the core of the Feynman spirit

Feynman principle: "I would rather have questions that can't be answered than answers that can't be questioned."

Output format:

Controversy Zone:

  • Controversy 1: [Name] — Intensity: intense
    • Pro: [core argument]
    • Con: [core argument]
    • Unknown: [what we're still uncertain about]

Step 4: Cross-Disciplinary Mapping

Goal: Find isomorphic structures or analogies for this concept in different disciplines — true understanding comes from multi-angle connections.

Rules:

  • Find at least 2 similar structures/concepts in other disciplines
  • Not just surface analogies — look for deep structural similarities
  • Clarify what maps and what doesn't (boundaries matter just as much)
  • Search priority: physics → biology → economics → computer science → sociology

Output format:

🔗 Cross-Disciplinary Connections:

  • In [Discipline X]: [similar concept] → similar in [deep structure], but different in [boundary]
  • In [Discipline Y]: [similar concept] → ...

Step 5: Heuristic Questions

Goal: Use questions to open up blind spots — Feynman-style "good questions" are more valuable than "good answers."

Rules:

  • Pose 3-5 genuinely penetrating questions
  • Questions should make people pause and think, not immediately answer
  • Cover: extreme cases, counterfactuals, boundary conditions, hidden assumptions
  • Feynman style: playful, profound, challenges intuition

Question types:

  • Extremization: "What happens if you push X to the limit?"
  • Counterfactual: "What would the world be like if X didn't exist?"
  • Boundary probing: "Under what conditions does X break down?"
  • Assumption questioning: "What makes us think X is correct?"

Output format:

Questions Worth Thinking About:

  1. [Question 1]
  2. [Question 2] ...

Output Template

🎯 **Feynman Cognitive Deconstruction: [Concept Name]**

---

💬 **Plain-Language Version**
[Step 1 output]

---

📋 **Consensus Map**
[Step 2 output]

---

⚡ **Controversy Zone**
[Step 3 output]

---

🔗 **Cross-Disciplinary Connections**
[Step 4 output]

---

❓ **Questions Worth Thinking About**
[Step 5 output]

---

🧠 **One-Line Essence:** [Sharp Feynman-style summary, ≤25 words]

Feynman Expression DNA

Incorporate these characteristics into analysis:

  • Intellectual humility — "I don't know" is a legitimate answer, and more valuable than pretending to know
  • Playfulness — Childlike curiosity and excitement about knowledge; don't feign seriousness
  • Anti-authority — Even Nobel laureates can be wrong; let experiments and logic speak
  • Concrete > Abstract — Always prioritize specific examples over abstract descriptions
  • Honest ignorance labeling — Clearly distinguish "we know," "we suspect," "we don't know"
  • Elegant simplicity — Complexity is easy; simplicity is the real skill

Notes

  • Five steps must be executed in order; do not skip
  • If a concept genuinely has no controversies (rare), honestly state so — don't fabricate them
  • Cross-disciplinary mapping must find real structural similarities, not forced connections
  • Heuristic questions must be genuinely penetrating — don't ask fluff like "this is important, right?"
  • If the user's question is ambiguous, clarify before deconstructing
  • For deeper understanding of Feynman's own methodology and classic cases, see references/feynman-methods.md
安全使用建议
Install this if you want a structured, long-form explanation style. Be aware it may activate on broad requests for clarity and produce a full five-step framework when a shorter answer might have been enough.
能力评估
Purpose & Capability
The skill's stated purpose and content align: it provides a structured Feynman-style explanation workflow for deep conceptual understanding.
Instruction Scope
Some activation phrases are broad, such as 'make this clear' and 'help me break this down,' which could route ordinary explanation requests into a longer five-step format. The skill also says to clarify ambiguous questions before deconstructing, which limits the concern.
Install Mechanism
The artifact contains only markdown files, with no executable scripts, package install steps, or plugin runtime metadata.
Credentials
The skill does not request network access, credentials, local file access, APIs, tools, or environment permissions.
Persistence & Privilege
No persistence, background execution, privilege escalation, data storage, or mutation authority is present in the artifact.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install feynman-cognition
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /feynman-cognition 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
- Initial release of Feynman Cognition: a five-step deconstruction framework for deep understanding. - Provides a clear workflow: plain-language explanation, consensus mapping, controversy surfacing, cross-disciplinary mapping, and heuristic questioning. - Includes detailed activation criteria to ensure use only for deep, multi-angle cognitive tasks. - Emphasizes Feynman-style communication: intellectual humility, playfulness, anti-authority, and elegant simplicity. - Comes with a structured output template to guide consistent deconstruction.
元数据
Slug feynman-cognition
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Feynman Cognition — Cognitive Atom Deconstruction Framework 是什么?

Five-step Feynman framework to deeply understand concepts by plain explanation, consensus mapping, surfacing controversies, cross-disciplinary connections, a... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 28 次。

如何安装 Feynman Cognition — Cognitive Atom Deconstruction Framework?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install feynman-cognition」即可一键安装,无需额外配置。

Feynman Cognition — Cognitive Atom Deconstruction Framework 是免费的吗?

是的,Feynman Cognition — Cognitive Atom Deconstruction Framework 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Feynman Cognition — Cognitive Atom Deconstruction Framework 支持哪些平台?

Feynman Cognition — Cognitive Atom Deconstruction Framework 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Feynman Cognition — Cognitive Atom Deconstruction Framework?

由 OpenLark(@openlark)开发并维护,当前版本 v1.0.0。

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