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First Rate Talent Coach

Community
ace3000chao
first-rate-talent-coach

用于领导力发展和个人绩效提升场景。当用户在讨论人才培养、管理者成长、要不要请教练时激活。 不适用于:纯技能培训讨论(那是培训部门范畴)、外部管理咨询采购决策。 关键 trigger:提到领导力瓶颈、管理困境、绩效辅导、高管教练。

Overview

Publisherace3000chao
Repositorybook2startup
Skill namefirst-rate-talent-coach
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 First Rate Talent Coach 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/ScalingUp-skills/first-rate-talent-coach
  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.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/ace3000chao/book2startup.git /tmp/book2startup
mkdir -p .claude/skills
cp -r /tmp/book2startup/ScalingUp-skills/first-rate-talent-coach .claude/skills/first-rate-talent-coach
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable First Rate Talent Coach 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 First Rate Talent Coach 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 First Rate Talent Coach 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.

First-Rate Talent Needs Coach

R — 原文 (Reading)

"No one has ever achieved peak performance without a coach."

— Verne Harnish, Scaling Up, 第5章


I — 方法论骨架 (Interpretation)

Scaling Up 的这个原则颠覆了一个常见认知:顶尖人才不需要监督,只需要教练。这是领导力从"管控"到"激发"转变的核心标志。

顶级运动员有教练,顶级CEO有教练,顶级音乐家有教练——因为教练能在你看不见自己的盲点时给你反馈,在你放弃时逼你再撑一次,在你需要战略视角时给你更高的观察点。

对于A类人才来说:他们已经知道怎么做好工作,真正需要的是一个能帮助他们突破当前天花板、进入下一个层级的对话者。这不是培训,不是指导,是一对一的深度教练。

关键区分:coach vs boss。boss 分配任务、检查结果;coach 发现潜能、拆掉限制、逼你成长。


A1 — 书中的应用 (Past Application)

案例 1: 某CEO的高管教练投资

  • 问题: 创始人从技术岗位成长到CEO,感觉在战略决策和团队领导上遇到了自己无法突破的瓶颈,但内部没有能辅导他的人。
  • 方法论的使用: 聘请了一位有两次CEO经验的前任企业家作为月度教练,每月4小时对话。一开始CEO觉得"我知道这些",三个月后发现自己的思维模式盲点。
  • 结论: 教练的价值不在于告诉你新知识,而在于用新视角拆解你的旧模式。
  • 结果: 一年后,这位CEO在团队领导力评估中的分数从65分提升到82分,公司年收入增长40%。

案例 2: 销售总监的绩效辅导重塑

  • 问题: 一位年销售额超过5000万的销售总监,团队有10人,但管理方式是一对一检查日报——实际上是用执行细节替代了真正的辅导。
  • 方法论的使用: 引入外部销售教练,对总监进行每月一次的"教练式对话"培训:从追问细节转向提问意图,从解决问题转向激发思考。总监开始用"你觉得这件事最好的处理方式是什么"替代"你打算怎么做"。
  • 结论: 教练技能帮助管理者从"给答案"转向"激发出答案"。
  • 结果: 6个月后,团队人均单产提升35%,销售总监自己的时间利用率提升了50%(不再被下属的细节汇报占据)。

A2 — 触发场景 (Future Trigger) ★

用户会在什么情境下需要这个 skill?

  1. 管理者晋升后遇到瓶颈时:用户说"升职后发现不知道怎么当领导了"或"以前管自己,现在管团队,不知道怎么管"。
  2. A类人才留不住时:对高潜人才的培养投入不足,导致他们感觉没有成长而离开。
  3. 讨论要不要请教练/导师时:在犹豫是否值得花这笔钱,教练和培训有什么区别。
  4. 绩效对话质量低下时:用户的团队成员在绩效评估时总是"意外"得知问题,缺乏日常辅导机制。
  5. CEO或创始人自我成长停滞时:企业发展到一定阶段,创始人的认知成为公司天花板。

语言信号 (用户的话里出现这些就应激活)

  • "领导力……"
  • "要不要请教练……"
  • "管理者培训……"
  • "带团队……"
  • "突破瓶颈……"
  • "辅导……"

与相邻 skill 的区分

  • 与 Hire Fewer, Higher Pay 的区别:少人高薪解决的是"招什么人、付多少钱"的配置问题,这个解决的是"如何让A类人才持续成长"的保留和发展问题。
  • 与 3:1 Positive Interaction Ratio 的区别:3:1原则是日常互动的质量配比,教练是一对一深度对话的专业关系——前者是每个管理者的日常习惯,后者是针对A类人才的高杠杆投资。

E — 可执行步骤 (Execution)

当 skill 被激活后,agent 应按以下步骤执行:

  1. 识别最需要教练的A类人才

    • 列出组织内前10-15%的关键人才(不只是管理层,也包括核心技术/业务骨干)
    • 问:这些人下一步成长需要突破的瓶颈是什么?是战略思维、团队领导、跨部门协作,还是自我认知?
    • 完成标准:锁定2-3个最有coach需求的高潜人才
  2. 选择合适的教练类型

    • 内部教练(高管团队成员兼任):适合有成熟高管团队的成长期公司,成本低但可能存在视角盲区
    • 外部专业教练(Certified Coach):适合高管层突破,适合需要绝对保密和安全空间的对话场景
    • 导师(曾在类似岗位取得成功的前辈):适合战略思维和行业经验传承,但导师关系容易变成闲聊而非深度教练
    • 判停条件:若用户已有明确的教练人选偏好(如"我想找有过创业经验的"),直接进入步骤3
  3. 设计教练对话的节奏和框架

    • 最小可行节奏:每月1次 × 2小时深度对话 × 至少6个月
    • 每次对话结构:上半月进展回顾 → 下半月挑战共创 → 下一个行动承诺
    • 完成标准:产出一份包含教练人选、节奏、预期成果的教练设计方案

B — 边界 (Boundary) ★

不要在以下情况使用此 skill

  • B/C类人才的首要问题不是教练:对于意愿不足或能力差距过大的人,教练对话是资源浪费——他们首先需要的是明确目标或更换岗位。
  • 关系信任尚未建立时:教练关系需要被辅导者对教练有足够信任,否则对话停留在表面。
  • 短期一次性咨询:教练的本质是长期关系(6个月起),不适合"今天有个问题想问问"的使用场景。

作者在书中警告的失败模式

  • 请了教练但不开绿灯——被辅导者不改变日常行为,教练对话变成"倾诉"而非"成长"。

作者的盲点 / 时代局限

  • 对中小企业能否负担专业教练费用(市场价3-10万/月)缺乏成本收益分析,书中案例多来自大公司。

容易混淆的邻近方法论

  • 3:1 Positive Interaction Ratio:3:1是每个管理者对每个下属的日常互动质量要求,coach是针对A类人才的一对一深度成长关系——前者是普遍要求,后者是高杠杆选择。

相关 skills (阶段 3 填充)

  • depends-on: [hire-fewer-higher-pay, 3x-positive-interaction-ratio]
  • contrasts-with: [3x-positive-interaction-ratio]
  • composes-with: [onboarding-culture-immersion]

审计信息

  • 验证通过: V1 ✓ / V2 ✓ / V3 ✓
  • 测试通过率: 待填充
  • 蒸馏时间: 2026-04-26

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 First Rate Talent Coach AI skill do?

用于领导力发展和个人绩效提升场景。当用户在讨论人才培养、管理者成长、要不要请教练时激活。 不适用于:纯技能培训讨论(那是培训部门范畴)、外部管理咨询采购决策。 关键 trigger:提到领导力瓶颈、管理困境、绩效辅导、高管教练。

Why use First Rate Talent Coach on TypingMind?

Because you install it once and use it with any model. First Rate Talent Coach 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 First Rate Talent Coach in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ace3000chao/book2startup/tree/master/ScalingUp-skills/first-rate-talent-coach. 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 First Rate Talent Coach?

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 First Rate Talent Coach?

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

Is the First Rate Talent Coach 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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