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F07 Timing Patience

Community
ace3000chao
f07 timing-patience

当用户说"为什么别人都成功了而我还没有"、"我都努力了这么久怎么还没结果"、"是不是我不够好"时调用。 也适用于:评估长期投入是否值得、判断"是否应该继续等待时机"、创业者和投资者评估项目节奏。 不适用于:用户只是在抱怨而非做决策、日常琐事选择、需要立即行动的紧急情况。

Overview

Publisherace3000chao
Repositorybook2startup
Skill namef07 timing-patience
Stars
93
Forks
14
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by ace3000chao on GitHub. Read the source before you install it.

Installation

Install the F07 Timing Patience AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/ace3000chao/book2startup/tree/master/菜根谭skills/skills/f07
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Use it in TypingMind

Enable F07 Timing Patience in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads F07 Timing Patience on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so F07 Timing Patience is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

见微知著守正待时

R — 原文 (Reading)

"伏久者飞必高,开先者谢独早;知此,可以免蹭蹬之忧,可以消躁急之念。"

— 洪应明, 菜根谭·见微知著 守正待时


I — 方法论骨架 (Interpretation)

比较的不是当下的快慢,而是最终的势能。

这个框架提供了两个反直觉的判断原则:

  1. "伏久者飞必高":潜伏得越久,一旦起飞飞得越高。那些看起来"一夜爆红"的人,实际上积累了很多年——他们只是在最近才遇到了适合他们的条件。不要因为暂时没有成果而低估长期积累的价值。
  2. "开先者谢独早":过早开始、过早加速的人,往往也过早衰败。太早成功往往意味着基础不稳、根基不深,容易在后续的竞争中败下阵来。

方法论本质:

  • 当你觉得自己"还没成功"时,问自己:我是在"伏久"(长期积累)还是在"落后"(原地踏步)?这两者的表面现象很相似,但本质不同。
  • 当你觉得自己"落后于他人"时,比较的不是当下的位置,而是最终的势能。

一句话总结: 不要用当下的快慢来判断最终的高度。


A1 — 书中的应用 (Past Application)

案例 1: 姜子牙钓鱼愿者上钩

  • 问题: 姜子牙年迈时还在渭水边钓鱼,看似"一事无成",同期的贤士早已有了好的归宿。
  • 方法论的使用: 姜子牙用"伏久者飞必高"的逻辑自我评估:他的才华和能力还没有遇到合适的时机(周文王),所以还在"潜伏期",这不是失败,而是在积累势能。
  • 结论: "伏久"不是"落后",而是"飞高之前的必经阶段"。
  • 结果: 姜子牙在80岁左右遇到周文王,一飞冲天,辅佐周朝八百年基业。他的"飞高"来自于几十年潜伏期的积累,而不是少年得志。

案例 2: 刘邦 vs 项羽

  • 问题: 项羽在楚汉之争初期占尽优势,巨鹿之战破釜沉舟,诸侯跪拜;刘邦则多次败北,狼狈逃窜。
  • 方法论的使用: 从"开先者谢独早"的角度看,项羽的过早辉煌(少年英雄、天下无敌)正是他后来败亡的预兆——他的成功太早,没有足够的政治积累来支撑帝业。而刘邦的"屡败"实际上是在积累政治资本、团队能力、民心向背。
  • 结论: 项羽的"开先"导致"谢独早";刘邦的"伏久"导致"飞必高"。
  • 结果: 刘邦建立汉朝,项羽乌江自刎。从最终的势能看,刘邦的"慢"赢了项羽的"快"。

A2 — 触发场景 (Future Trigger) ★

用户会在什么情境下需要这个 skill?

  1. 长期努力但没有成果:用户已经坚持了很久(项目、事业、学习),但看不到明显的进步或突破,开始怀疑是否应该继续。
  2. 与同龄人比较后焦虑:看到别人"年少成名"(融资、上市、暴富),感觉自己落后了,想放弃现在的方式去追热点。
  3. 阶段性评估"是否应该继续等待":创业者在漫长的投入期想知道"还要等多久";职场人在看不到晋升通道时想知道"是否该转方向"。
  4. 想要理解"为什么我还没成功":用户想找一个框架来理解自己的处境,避免陷入自我否定或焦虑。
  5. 评估他人的"成功"是否可持续:用户看到别人"一夜成名"或"快速崛起",想判断这是"真正的起飞"还是"早谢的风险"。

语言信号 (用户的话里出现这些就应激活)

  • "为什么别人都成功了而我还没有"
  • "我都努力了这么久怎么还没结果"
  • "是不是我不够好所以还没成功"
  • "我是不是落后太多了"
  • "看别人这么年轻就成功了,我很焦虑"
  • "这个方向我要坚持多久才能看到结果"
  • "我已经等了很长时间了,还要继续等吗"
  • "他这么年轻就这么厉害,是不是我哪里做错了"

与相邻 skill 的区分

  • 与 f05(净从秽生转化框架) 的区别:f05 关注"污秽中可以转化",重点是"如何把低潮变成成长";f07 关注"潜伏期要多久才结束",重点是"如何判断时机是否到来"。f05是转化路径,f07是时机判断。
  • 与 f13(逆增上缘修行框架) 的区别:f13 讲"逆境是修行的机会";f07 讲"潜伏期是起飞的前奏"。f13是在逆境中寻找价值,f07是在等待中保持信心。
  • 与 f20(以失意之思制得意之念) 的区别:f20 用时间透视法来稀释当下的执念(以老视少);f07 用势能比较来回答"该不该继续等待"的问题。

E — 可执行步骤 (Execution)

当 skill 被激活后,agent 应按以下步骤执行:

  1. 区分"伏久"还是"原地踏步"

    • 完成标准: 明确说出"你是处于积累期(伏久)还是重复期(原地踏步)",判断标准是:过去一段时间,你的能力、见识、资源是否在持续增长?即使成果还没显现。
    • 判停条件: 若用户无法回答(无法评估自己是否有成长),则进入下一步的"外部视角对比"。
  2. 用"最终势能"代替"当下快慢"来评估

    • 完成标准: 让用户列出"如果继续当前方向,3年后我会积累什么?这些积累是否有价值?"对比"如果换方向,3年后我会积累什么?"用势能比较代替当下快慢的比较。
    • 判停条件: 若用户发现当前方向确实没有势能积累,则提示"这不是'伏久',是'迷途',需要重新选择方向"。
  3. 建立"等待期"的具体计划

    • 完成标准: 和用户一起制定"继续等待期间的具体行动"——不是被动等待,而是"在潜伏期我应该做什么来增加将来起飞的高度"。
    • 判停条件: 若用户已经处于极度焦虑状态(无法思考具体行动),则提示"先休息,再计划"。

B — 边界 (Boundary) ★

不要在以下情况使用此 skill

  • 用户的方向本身就是错误的:如果用户在走一条没有发展潜力的路,"伏久者飞必高"可能被滥用为"继续坚持就会成功"的理由,成为自我欺骗的工具。
  • 用户处于生存危机:如果用户的经济/生活状况已经不允许继续等待,需要立即获得回报,此时不应鼓励继续等待,而应帮助用户重新评估方向。
  • 用户已经用这个框架自我欺骗超过5年:如果一个用户长期用"时机未到"来回避面对现实问题,这个框架已经被滥用了,需要引入更直接的干预。

作者在书中警告的失败模式

  • 快意不知回首(ce03):春风得意时不知见好就收,贪恋权位不肯急流勇退。表现为处于巅峰时愈发贪婪、不愿接受任何退让。"开先者谢独早"的反面就是"得意时不知退"——太早的成功往往是早衰的前兆。
  • 躁性偾事(ce09):性躁心粗者一事无成,表现为做事总是很着急、不愿在细节上下功夫、情绪波动大。f07的核心是"不急躁",ce09正好是f07要对治的问题。

容易混淆的邻近方法论

  • "守正待时" vs "守株待兔":守正待时是在正确的方向上持续积累,等待时机成熟;守株待兔是在错误的方向上消极等待,指望运气救自己。f07要求的是"方向正确+持续积累",不是"什么都不做等运气"。
  • "伏久飞必高" vs "盲目坚持":f07的前提是方向正确、能力在增长;盲目坚持是方向错误或能力没有进步。"伏久"的定义是"积累中",不是"苦熬中"。

相关 skills (阶段 3 填充)

  • depends-on: []
  • contrasts-with: [f05, f13, f20]
  • composes-with: [f05, f01]

审计信息

  • 验证通过: V1 ✓ / V2 ✓ / V3 ✓
  • 测试通过率: N/A (待填充)
  • 蒸馏时间: 2026-04-24

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the F07 Timing Patience AI skill do?

当用户说"为什么别人都成功了而我还没有"、"我都努力了这么久怎么还没结果"、"是不是我不够好"时调用。 也适用于:评估长期投入是否值得、判断"是否应该继续等待时机"、创业者和投资者评估项目节奏。 不适用于:用户只是在抱怨而非做决策、日常琐事选择、需要立即行动的紧急情况。

Why use F07 Timing Patience on TypingMind?

Because you install it once and use it with any model. F07 Timing Patience is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install F07 Timing Patience in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ace3000chao/book2startup/tree/master/菜根谭skills/skills/f07. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use F07 Timing Patience?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with F07 Timing Patience?

As many as you like. As long as a model supports skills, you can use F07 Timing Patience with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the F07 Timing Patience AI skill free?

Yes. It is published on GitHub by ace3000chao under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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