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Agent Skill · 开发

first-principles-thinking(第一性原理思维)

first-principles-thinking 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

first-principles-thinking 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 16,391。

总安装 509周安装 21GitHub Stars 6下载 166核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:first-principles-thinking(第一性原理思维)
来源仓库:https://github.com/andurilcode/skills
仓库路径:skills/first-principles-thinking
安装命令:
npx skills add https://github.com/andurilcode/skills --skill first-principles-thinking
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/andurilcode/skills --skill first-principles-thinking

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

剥离假设与行业惯例,从基础物理定律或数学原理出发重构解决方案,寻找本质最优路径。适用于突破思维定式、重新设计复杂系统或成本优化问题,如 SpaceX 火箭制造案例。分三步:明确当前信念、挑战所有假设、重建基于 fundamentals 的新方案。需警惕“群体思维”与“类比陷阱”,鼓励质疑常识性前提。

适合创新类项目,但在时间紧迫或知识边界不清时不建议使用。

来源仓库内路径:skills/first-principles-thinking

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/andurilcode/skills --skill first-principles-th…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

first-principles-thinking 怎么安装?

在终端执行 npx skills add https://github.com/andurilcode/skills --skill first-principles-thinking。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

first-principles-thinking 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

first-principles-thinking 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

first-principles-thinking 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

first-principles-thinking 用的人多吗?

公开数据是累计安装 509 次,近一周安装 21 次,下载 166 次,GitHub 6 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

first-principles-thinking 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
first-principles-thinking

第一性原理思维 · 本页

5096需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

First Principles Thinking

Core principle: Strip away assumptions, conventions, and analogies. Reduce everything to the fundamental truths you *know* to be true, then rebuild from there. Most thinking is by analogy — "we do it this way because that's how it's done." First principles asks: *why is it done that way at all?*


The Core Process

Step 1: Identify the Current Belief or Solution

State clearly what is currently assumed, accepted, or proposed:

  • What is the existing approach?
  • What problem is it trying to solve?
  • What does everyone in this space assume to be true?

Step 2: Challenge Every Assumption

For each element of the current approach, ask:

  • *"Is this actually true, or do we believe it because we've always believed it?"*
  • *"Is this a constraint of reality, or a constraint of convention?"*
  • *"What would have to be true for this assumption to be wrong?"*

Distinguish between:

  • Physical constraints: Laws of nature, math, physics — these are real
  • Resource constraints: Time, money, people — real but changeable
  • Conventional constraints: "You can't do X" meaning "nobody has done X yet"
  • Inherited assumptions: Decisions made for past conditions that no longer apply

Step 3: Identify the Fundamental Truths

What do you *actually* know, stripped of convention?

  • What is the core need being served?
  • What are the irreducible requirements?
  • What would this look like if you designed it from zero, knowing only what's physically true?

Step 4: Rebuild From the Ground Up

Starting only from fundamental truths, reconstruct the solution:

  • What's the simplest approach that satisfies the real requirements?
  • What would this look like if invented today, with today's capabilities?
  • What existing constraints can be eliminated now that you're not inheriting them?

Output Format

🏛️ Current Belief / Approach

State what's being questioned:

  • The existing design, strategy, or assumption
  • Why it exists (historical or conventional reason)
  • What problem it was meant to solve

🔬 Assumption Deconstruction

For each major assumption:

AssumptionTypeActually true?Evidence
"We need X to do Y"ConventionalMaybe notReason
"This requires Z"PhysicalYesBecause...
"Users expect A"InheritedUnvalidatedNever tested

🧱 Fundamental Truths Identified

What do we *actually* know, independent of convention?

  • Core need: [The real underlying need being served]
  • Hard constraints: [What is genuinely immovable]
  • Validated facts: [What has been empirically confirmed]

🔨 Rebuilt Solution

Starting from fundamentals:

  • What does the solution look like without inherited assumptions?
  • What changes dramatically?
  • What stays the same (and why — what fundamental truth supports it)?
  • What's now possible that wasn't in the old frame?

⚠️ Assumption Risks

Which surviving assumptions are highest-risk?

  • If any single assumption proves wrong, what breaks?
  • Which assumptions should be validated before committing?

Thinking Triggers

  • *"What is this actually trying to accomplish at the most basic level?"*
  • *"If we were building this today with no legacy, what would we do?"*
  • *"Is this a law of nature or a law of habit?"*
  • *"Who decided this was the right way, and what were their constraints?"*
  • *"What would a brilliant outsider — who doesn't know our conventions — suggest?"*
  • *"Are we solving the problem, or are we solving our version of the problem?"*

Analogy vs. First Principles

Most thinking operates by analogy:

*"We do it like company X does it"* / *"The industry standard is Y"* / *"That's how it's always been done"*

Analogy-based thinking is fast and usually adequate. But it inherits the constraints and mistakes of the original. When something is fundamentally broken or when you need a step-change improvement — not an incremental one — analogy thinking will never get you there.

First principles is slower but the only path to genuinely novel solutions.


Example Applications

  • "Should our agent pipeline be sequential?" → Why sequential? What's the fundamental constraint? Is it ordering of dependencies, or just convention borrowed from waterfall?
  • "We need a dedicated QA team" → Is QA a separate function by necessity, or because testing was historically slow and manual?
  • "Our API needs versioning" → What's the actual need — backward compatibility. What's the minimum mechanism that provides that, built from scratch?
  • "We need standups every day" → What's the fundamental need? Coordination. What are all the ways to achieve that, unconstrained by "meeting" as a format?

平台分布

Codex

35.75%
按下载量换算59

Claude

30.22%
按下载量换算50

Cursor

16.17%
按下载量换算27

Gemini CLI

8.56%
按下载量换算14

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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