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Hierarchical Face Exchange

Community
MichaelRochonnn
hierarchical-face-exchange

在层级制组织中,当需要向高级别高管汇报或展示成果时,通过让老板代为汇报来建立长期信任和地位。适用于初级顾问、下属或远离总部的团队成员,避免因资历不足而在高管面前失去可信度。

Overview

PublisherMichaelRochonnn
Repositorymckinsey-bcg-consulting
Skill namehierarchical-face-exchange
Stars
77
Forks
16
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Hierarchical Face Exchange 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/MichaelRochonnn/mckinsey-bcg-consulting/tree/main/hierarchical-face-exchange
  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/MichaelRochonnn/mckinsey-bcg-consulting.git /tmp/mckinsey-bcg-consulting
mkdir -p .claude/skills
cp -r /tmp/mckinsey-bcg-consulting/hierarchical-face-exchange .claude/skills/hierarchical-face-exchange
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hierarchical Face Exchange 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 Hierarchical Face Exchange 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 Hierarchical Face Exchange 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.

层级制度中的面子交换原则

适用场景

当满足以下条件时使用此技能:

  • 你处于层级制组织中
  • 需要与等级森严的公司高管分享成果
  • 你相对资深人士显得太"嫩"(如入职一年的顾问)
  • 老板是团队中唯一能注意到你表现的人

不适用场景:

  • 完全扁平化组织
  • 老板明确表示希望你直接汇报

核心原则

在层级制度中,面子是交换货币:

  • 让老板脸上有光 → 老板让你有面子
  • 正如发型师法则:"你的老板脸上有光,你就脸上有光"

执行步骤

1. 评估老板的重要性等级

  • 基础情况:在任何层级制组织中,每天老板都是你世界里最重要的人
  • 升级情况:当团队在偏远城市或异国他乡远离公司时,老板重要性再上升一个等级(她可能是唯一注意到你的人)

2. 执行"代汇报"协议

步骤A:准备综合分析资料

  • 作为初级人员,花几周时间准备深度分析(如竞争对手分析)
  • 确保内容质量高、逻辑严密

步骤B:识别限制

  • 认识到直接分享会显得你太"嫩"
  • 需要由项目经理(你的老板)来做汇报

步骤C:接受情绪

  • 接受失望情绪但理解这是层级制度的合理运作方式

步骤D:深度知识同步(关键步骤)

  • 花几个小时让项目经理对内容的了解和你一样熟悉
  • 确保老板能自信地回答所有问题

步骤E:支持老板成功

  • 确保第二天项目经理能做很有说服力的演讲
  • 在汇报过程中提供必要的支持

3. 双赢验证

确认此举对你和老板一样有益处:

  • 老板获得高管的认可
  • 你获得幕后贡献者的信任
  • 建立长期的组织地位
  • 避免在高管面前暴露资历不足的弱点

关键变量

  • hierarchy_level(组织层级强度):1-10级,影响面子交换的显著性
  • geographic_distance(与总部的地理距离):本地/偏远城市/异国
  • preparation_hours(让老板熟悉内容所需的准备时间):通常为几个小时

预期结果

老板成功完成高层汇报并获得认可,你获得幕后贡献者的信任和未来的面子回报,避免在高管面前暴露资历不足的弱点。

Frequently asked questions

What does the Hierarchical Face Exchange AI skill do?

在层级制组织中,当需要向高级别高管汇报或展示成果时,通过让老板代为汇报来建立长期信任和地位。适用于初级顾问、下属或远离总部的团队成员,避免因资历不足而在高管面前失去可信度。

Why use Hierarchical Face Exchange on TypingMind?

Because you install it once and use it with any model. Hierarchical Face Exchange 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 Hierarchical Face Exchange in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/MichaelRochonnn/mckinsey-bcg-consulting/tree/main/hierarchical-face-exchange. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Hierarchical Face Exchange?

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 Hierarchical Face Exchange?

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

Is the Hierarchical Face Exchange AI skill free?

It is published on GitHub by MichaelRochonnn. Check the repository for licensing terms. 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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