摆脱自我意识三步法

摆脱自我意识三步法 is a skill for Claude Code, Codex from R2h1/my-book-skills. It costs 100 tokens per session (2,018 once invoked), scanned A, original, MIT.

A three-step reflection method for handling defensiveness, envy, or excuses when facing unfamiliar information or someone else's success.

In plain words
What is it for?
Use it when someone dismisses a new idea, envies another person's success, or blames outside factors after failure.
Why use it?
It helps users notice their reaction, acknowledge its cause, and turn it into a chance to learn instead of rejecting the information.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it when someone dismisses a new idea, envies another person's success, or blames outside factors after failure.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/r2h1/my-book-skills/v01
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add R2h1/my-book-skills --skill v01
Clone the repo
git clone --depth 1 https://github.com/R2h1/my-book-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

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README.md
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<a href="https://agentmods.dev/skills/r2h1/my-book-skills/v01"><img src="https://agentmods.dev/badge/skills/r2h1/my-book-skills/v01.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 100 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,018 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00100 $0.02018
Opus 5 $0.00050 $0.01009
Sonnet 5 $0.00020 $0.00404
Haiku 4.5 $0.00010 $0.00202

Measured 11d ago against content hash 841346aa583f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

摆脱自我意识三步法 scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

30岁人生开挂7步法/v01-摆脱自我意识三步法/SKILL.md · 141 lines

How it starts

The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.

摆脱自我意识三步法

R — 原文

"大多数人为了保护自我,一辈子都在用各种防御机制抵制陌生的信息。如果不摆脱你的自我意识,你就不可能有任何进步。这也是大多数聪明的人从一定的年龄开始就只会'责怪别人',永远也不会进步的原因。"

— 金承焕, 第二章


I — 方法论骨架

自我意识是人保护自尊的本能防御机制,但过度时它会阻止一切成长。当接收到与自己现有认知不符的信息时,自我意识自动启动:贬低信息源、找借口推脱、伪装清高。这个方法论的核心是一个三步骤循环:

  1. 探索 — 察觉到自己的情绪变化(嫉妒、反感、不屑),追问"这个情绪从何而来?"
  2. 认可 — 客观审视原因,该承认的承认("我嫉妒她的成功""我确实不懂这个领域")
  3. 转换 — 将防御模式切换为学习模式("我能从中学到什么?""我需要提高什么?")

关键洞察:自我意识不会消失,但可以被识别和绕开。你不是要"消灭自我",而是要在它启动防御时及时发现并手动切换模式。


A1 — 书中的应用

案例 1: 智英放弃设计自尊心

  • 问题: 20多岁的设计师智英,对设计有自信但多年未获收益,陷入"设计自尊心"的陷阱
  • 方法论的使用: 作者建议她"摆脱自我意识"——放弃"我是艺术家"的身份执念,先做LOGO生意赚钱
  • 结论: 智英起初受打击不愿承认,但最终接受现实
  • 结果: 打造了月均净收入3000万韩元以上的企业,拥有15名以上员工

案例 2: 姣媛从嫉妒到学习

  • 问题: 33岁的姣媛嫉妒26岁的女企业家智慧,怀疑对方夸大收入,导致聚会解散
  • 方法论的使用: 作者点醒她这是自我意识作祟,她承认嫉妒后发长短信向智慧道歉
  • 结论: 从防御模式切换到学习模式
  • 结果: 两人成为至亲,姣媛学到智慧的优点,成为月入6000万韩元的企业家

案例 3: 首尔大学A的自我意识悲剧

  • 问题: 首尔大学毕业生A无法接受成绩中下游,归因于"同学家境好""不公平"
  • 方法论的使用: 从未使用——他持续用自我意识防御,拒绝承认自身不足
  • 结论: 反面案例——不摆脱自我意识的后果
  • 结果: 生意失败、人脉枯竭,只能重复强调自己是首尔大学出身

A2 — 触发场景

用户会在什么情境下需要这个 skill?

  1. 别人介绍一个新方法/新机会时,第一反应是找理由否定
  2. 看到别人成功时感到嫉妒、不屑或想"找黑点"
  3. 失败后立刻想辩解或找替罪羊

语言信号

  • "他不过是运气好/有背景"
  • "这些我都知道"
  • "我干过,这个不行"
  • "这不是我的问题,是因为……"
  • "钱不重要/价值比钱重要"(回避赚钱话题)

与相邻 skill 的区分

  • Kluge识别与对抗法 的区别: 自我意识是"身份层面的防御"(不想承认自己需要改变),Kluge是"本能层面的误指挥"(进化遗留的恐惧/偏见)。前者处理"面子",后者处理"本能"

E — 可执行步骤

当 skill 被激活后,agent 应按以下步骤执行:

  1. 探索 — 定位情绪来源

    • 引导用户描述具体情境:"当听到/看到什么时,你产生了什么感觉?"
    • 帮助用户区分"事实"和"情绪反应":这件事本身是什么,你的感受又是什么
    • 完成标准: 用户能说清"我对XX感到嫉妒/反感/不屑"
  2. 认可 — 客观承认现实

    • 引导问:"抛开情绪,对方说的话/做的事中,有没有哪怕一部分是事实?"
    • 帮助用户承认具体需要承认的事情(能力不足、认知有限、嫉妒等)
    • 完成标准: 用户能用"我承认……"句式说出一句客观事实
    • 判停条件: 如果用户持续否认且情绪激烈,说明防御机制过强,回到步骤1加深探索
  3. 转换 — 制定学习行动

    • 引导问:"从这个情境中,我能学到什么?我需要提高什么?"
    • 帮用户制定一个最小的学习行动(读一篇文章、尝试一个新方法)
    • 完成标准: 用户确定了一个具体的下一步行动

B — 边界

不要在以下情况使用此 skill

  • 用户正在经历严重的情绪危机或心理创伤——此时需要的是支持而非认知重构
  • 用户已经被长期PUA或处于虐待关系——"承认自己不足"可能被滥用为自我归咎
  • 用户的需求只是信息查询——不需要进行心理干预

作者在书中警告的失败模式

  • "自我意识僵尸":防御机制完全固化,变成永远在否定一切的老顽固——键盘侠、习惯性贬低成功人士(ce19)
  • 用"我干过,我知道"的一两次负面经验否定整类事物(ce11)
  • 找替罪羊代替自我反思,错失从错误中学习的机会(ce04)

Read the full file on GitHub · 141 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 141 lines · 100 tokens per session scan A 841346aa583f

Subscribe to this mod's changes

摆脱自我意识三步法 is a skill published in the GitHub repository R2h1/my-book-skills (2 stars, last pushed 26d ago), licensed MIT. It adds 100 tokens to every session and 2,018 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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