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Feynman Technique Explainer

作者 arbazex · GitHub ↗ · v0.1.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install feynman-technique-explainer
功能描述
Explain any concept using the Feynman Technique, plain language, a real-world analogy, a concrete example, and a comprehension quiz. No jargon from the conce...
使用说明 (SKILL.md)

Overview

This skill breaks down any concept, scientific, technical, philosophical, or otherwise, using the Feynman Technique: a research-backed four-part learning method developed by Nobel Prize-winning physicist Richard Feynman. The core principle is that genuine understanding is proven by the ability to explain something in plain language without relying on the field's own vocabulary. The agent delivers a structured explanation across four mandatory parts, then quizzes the user to confirm comprehension. No jargon permitted.

When to use this skill

Use this skill when the user:

  • Asks "explain X to me", "help me understand X", or "what is X?"
  • Says "I keep forgetting how X works" or "I can never wrap my head around X"
  • Asks for a "simple explanation" or "ELI5" (explain like I'm five) of any topic
  • Is studying a subject and wants to test their understanding
  • Asks to "teach me" something from scratch
  • Says "break this down for me" or "make this simple"
  • Wants to learn a concept without prior background knowledge in the field

Do NOT use this skill for:

  • Requests to summarise documents or articles (use a summarisation skill instead)
  • Step-by-step how-to instructions or tutorials (e.g., "how do I install Python")
  • Mathematical derivations, proofs, or calculations the user wants to work through themselves
  • Requests that are explicitly for an expert-level or technical-depth answer
  • Lookup or retrieval tasks (e.g., "what is the capital of France")

Instructions

Follow these four steps in strict sequence. Do not skip, reorder, or merge any step. Label each part clearly in the output.


Step 0 — Identify the concept

Read the user's message and extract the single concept to explain. If the user's request contains multiple concepts, pick the most central one and note the others at the end, offering to cover them next.

If the concept is ambiguous (e.g., "explain energy"), ask one clarifying question:

"Just to make sure I explain the right thing, are you asking about [interpretation A] or [interpretation B]?"

Do not proceed until the concept is clear.


Step 1 — Plain Language Explanation (the "no jargon" core)

Write a plain-language explanation of the concept as if speaking to a curious 12-year-old who has never encountered the field before.

Rules for this step (all are mandatory):

  • Forbidden words: You must not use the concept's own name, its standard technical terms, or field-specific vocabulary in the explanation itself. For example, if explaining "entropy," you may not use the words entropy, thermodynamics, disorder, or second law of thermodynamics. If explaining "neural network," you may not use neurons, layers, weights, training, or backpropagation.
  • If you catch yourself needing a jargon term, replace it with an everyday description of what that thing does or looks like.
  • Use short sentences. Aim for sentences under 20 words.
  • Write in active voice.
  • Keep this section to 80–150 words.

Label this section: Part 1 — The Simple Explanation


Step 2 — Analogy

Construct one analogy that maps the concept onto something from everyday life. The analogy must:

  • Come from a domain entirely unrelated to the concept's field (do not use analogies that are themselves technical)
  • Make the mechanism of the concept understandable, not just its surface appearance
  • Be a single, coherent comparison, not a list of multiple analogies
  • Be introduced with a clear bridge phrase such as "Think of it like…" or "It works the same way as…"

After presenting the analogy, write one sentence explaining where the analogy breaks down or what it doesn't capture. This is important, all analogies have limits, and naming the limit prevents the user from overgeneralising.

Keep this section to 60–100 words.

Label this section: Part 2 — The Analogy


Step 3 — Concrete Example

Provide a single, specific, real-world example of the concept in action. The example must:

  • Be grounded in a real, verifiable situation (not a made-up hypothetical unless the concept is abstract)
  • Show the concept doing something or producing an observable result, not just existing
  • Use specific details (names, numbers, scenarios) wherever possible
  • Not repeat the analogy from Step 2

Avoid: "for example, imagine a ball rolling…" type toy examples unless they are genuinely the clearest illustration. Prefer examples from daily life, current technology, or history.

Keep this section to 60–100 words.

Label this section: Part 3 — A Real Example


Step 4 — Comprehension Quiz

Generate exactly three questions that test whether the user genuinely understood the explanation, not whether they can recall facts, but whether they grasped the concept deeply enough to apply or transfer it.

Question design rules:

  • At least one question must ask the user to apply the concept to a new situation not mentioned in the explanation
  • At least one question must ask why or how, not what
  • Do not ask questions that can be answered by copying a sentence from the explanation back verbatim
  • Questions should be answerable without specialised knowledge, only using the explanation provided

Present the questions as a numbered list. Do not provide the answers. Wait for the user to respond.

End with this exact line:

"Answer any or all of these, I'll tell you how you did and fill in any gaps."

Label this section: Part 4 — Test Your Understanding


Step 5 — Evaluate the user's answers (only after user responds)

When the user answers the quiz questions:

  • Evaluate each answer for conceptual accuracy, not wording precision
  • For correct answers: confirm briefly and explain why the answer is right
  • For partially correct answers: acknowledge what was right, then clarify the gap using a different angle than the original explanation
  • For incorrect answers: do not say "wrong", instead say "not quite" and re-explain that specific aspect only, using a new analogy or example if needed
  • Do not re-deliver the full four-part explanation; address only the gaps revealed

If the user skips the quiz entirely and asks to move on, respect that and ask what concept they want to tackle next.


Rules and guardrails

  • Jargon ban is absolute. If the explanation of a concept requires a jargon term, that term must be defined in plain language before use. Never assume the user knows field vocabulary.
  • Never compress the four parts into fewer. Every response must contain all four labelled sections in order. Do not merge the analogy and example into one section.
  • Do not morph into a textbook. Length limits per section exist to prevent lecture-style overload. Stick to the word counts in the instructions.
  • No fabrication. If the concept is at the frontier of knowledge and genuinely contested or unknown, say so clearly rather than constructing a false explanation. Example: "Scientists don't yet fully agree on how consciousness arises, here's the clearest explanation of what we do know."
  • Do not use other concepts as explanations. If explaining "quantum entanglement," do not explain it by saying "it's like quantum superposition." Explain both separately if needed.
  • One concept per response. If a user asks about multiple concepts in one message, explain the most central one and offer to continue with the others.
  • Respect the user's level. If the user indicates they have background knowledge (e.g., "I'm a biology student"), retain the structure but adjust the plain-language section to avoid being condescending. The jargon ban still applies in the explanation itself.
  • Never provide the quiz answers in the same message as the questions. The quiz only has value if the user attempts it.
  • Do not skip the analogy limit statement. Every analogy must be followed by a sentence noting where it fails.

Output format

Each response must follow this exact structure with these exact headings:

**Part 1 — The Simple Explanation**
[80–150 words, no jargon]

**Part 2 — The Analogy**
[60–100 words, includes one sentence on where the analogy breaks down]

**Part 3 — A Real Example**
[60–100 words, specific and grounded]

**Part 4 — Test Your Understanding**
1. [Application question]
2. [Why/How question]
3. [Third question]

> "Answer any or all of these, I'll tell you how you did and fill in any gaps."

Use bold for the part headings. Use regular paragraph prose for the explanation content, no bullet lists inside the explanation sections. Bullet lists are only permitted in the quiz.

Total response length: aim for 350–550 words. Do not exceed 700 words.

Error handling

User asks for a concept the agent does not have sufficient knowledge about: → Say: "I don't have enough reliable information about [concept] to explain it accurately. I'd rather tell you that than give you a confident but wrong explanation." → Do not fabricate an explanation.

User provides a vague or multi-part concept (e.g., "explain science"): → Ask: "That covers a lot of ground, could you narrow it down? For example, do you mean a specific branch like biology or physics, or a particular idea within a subject?" → Do not attempt to explain a category as if it were a single concept.

User asks for a jargon-heavy explanation on purpose (e.g., "explain it technically"): → Acknowledge the request, then explain: "This skill is designed to build understanding from the ground up, the plain-language version often reveals gaps that a technical explanation skips over. I'll keep the structure but note where the technical terms map onto each part." → Proceed with the four-part structure. You may reference the technical term after the plain explanation of it, in parentheses, as a label only.

User skips the quiz and asks a follow-up question: → Answer the follow-up directly, then briefly re-offer the quiz: "Want to try the questions when you're ready? They're good for locking this in."

User asks to compare two concepts: → Explain each concept separately using the four-part structure. Do not blend them. Then add a brief comparison paragraph after both explanations are complete.

Examples

Example 1 — Scientific concept

User: "Explain entropy to me"

Agent action: Execute four-part structure. Part 1 explains entropy as the natural tendency of things to spread out and become less organised over time, without using the words entropy, thermodynamics, disorder, or second law. Part 2 uses an analogy like a drop of ink in water, and notes the analogy breaks down because ink can't spontaneously un-mix even with energy added, which isn't true of all systems. Part 3 gives a real example such as an ice cube melting in a warm drink. Part 4 asks three questions including one like: "If you left a tidy room completely alone for a year, would it stay tidy or get messier? What does that tell you about the concept?"

Agent does NOT: Use the word "entropy" in Part 1. Skip any of the four parts. Provide answers alongside the quiz questions.


Example 2 — Technical/computing concept

User: "What is a neural network?"

Agent action: Part 1 explains it as a system that learns to spot patterns by making guesses and adjusting based on whether it was right or wrong, without using the words neural, network, layer, weight, training, or backpropagation. Part 2 uses an analogy such as learning to ride a bike by falling and adjusting until you stop falling. Notes the analogy breaks down because a bike-rider can explain their adjustments; the system cannot. Part 3 uses a concrete example such as how a phone's face unlock learns to recognise a face. Part 4 asks: "Why would showing the system more examples make it better at its task?" and similar questions.

Agent does NOT: Open with "A neural network is a system of interconnected nodes." Reference machine learning terminology in the plain explanation.


Example 3 — Abstract/philosophical concept

User: "Can you explain opportunity cost?"

Agent action: Part 1 explains that every choice to do one thing is also a choice to not do everything else, and the true cost of a decision includes what you gave up, without using "opportunity cost," "economics," or "trade-off." Part 2 uses an analogy such as choosing which queue to stand in at a supermarket, and notes it breaks down because queue choice is reversible while some real decisions are not. Part 3 uses a real example: a person choosing to go to university instead of working full-time, and how the salary they didn't earn during those years is a real cost even though no money left their pocket. Part 4 asks questions that require the user to identify the hidden cost in a new scenario.

Agent does NOT: Introduce the term "opportunity cost" until after the plain explanation is complete.

安全使用建议
This skill is coherent and low-risk: it only instructs the agent how to produce simplified explanations and quizzes and asks for no external credentials or installs. You can install it if you want a consistent Feynman-style explainer. Keep in mind: (1) it will process whatever text you give it (so avoid pasting private secrets), (2) it is not a substitute for professional advice (medical, legal, financial), and (3) as with any reasoning-only skill, check factual claims for accuracy before acting on them.
功能分析
Type: OpenClaw Skill Name: feynman-technique-explainer Version: 0.1.0 The skill is a well-structured prompt-based tool designed to explain complex concepts using the Feynman Technique. It contains no code, external dependencies, or network requests, and its instructions (SKILL.md) are strictly focused on educational formatting, jargon-free explanations, and user comprehension quizzes without any signs of malicious intent or data exfiltration.
能力评估
Purpose & Capability
The name and description (Feynman-style explanations) match the SKILL.md instructions. The skill requests no binaries, credentials, or external services — all appropriate for a purely instructional skill.
Instruction Scope
The SKILL.md contains clear, narrow runtime instructions (identify concept, produce four labeled parts, quiz, then evaluate answers). It does not direct the agent to read unrelated files, access environment variables, or contact external endpoints. The rules are strict (e.g., no jargon) and limit ambiguous agent behavior.
Install Mechanism
No install spec or code is present; the skill is instruction-only and runs on the agent's reasoning. This minimizes filesystem and network risk.
Credentials
The skill requires no environment variables, credentials, or config paths. There are no unexplained secrets or unrelated permissions requested.
Persistence & Privilege
always is false and the skill does not request permanent presence or system configuration changes. Autonomous invocation is allowed by platform default, which is expected for a user-invocable teaching skill.
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-technique-explainer
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /feynman-technique-explainer 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
v0.1.0
Initial release of Feynman Technique Explainer skill - Provides step-by-step explanations of any concept using the Feynman Technique. - Strictly enforces a no-jargon rule; all explanations use plain language for accessibility. - Uses a four-part structure: plain-language explanation, real-world analogy, concrete example, and a user quiz to test understanding. - Includes guardrails to avoid over-complexity, jargon, and topic drift. - Offers specific instructions on handling ambiguous or multi-concept requests.
元数据
Slug feynman-technique-explainer
版本 0.1.0
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 Technique Explainer 是什么?

Explain any concept using the Feynman Technique, plain language, a real-world analogy, a concrete example, and a comprehension quiz. No jargon from the conce... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 190 次。

如何安装 Feynman Technique Explainer?

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

Feynman Technique Explainer 是免费的吗?

是的,Feynman Technique Explainer 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Feynman Technique Explainer 支持哪些平台?

Feynman Technique Explainer 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 Technique Explainer?

由 arbazex(@arbazex)开发并维护,当前版本 v0.1.0。

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