Moat Strength Review Skill logo

Moat Strength Review Skill

Organization
Wind-Alice
moat_strength_review_skill

评估公司竞争优势的来源、强度、可持续性与削弱风险,判断护城河是否真实存在并能转化为回报。适用于长线票初筛、优质公司研究、竞争壁垒判断等场景。

Overview

PublisherWind-Alice
RepositoryAliceMarket
Skill namemoat_strength_review_skill
Stars
135
Forks
18
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 Wind-Alice on GitHub. Read the source before you install it.

Installation

Install the Moat Strength Review Skill 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/Wind-Alice/AliceMarket/tree/main/skills/moat_strength_review_skill
  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/Wind-Alice/AliceMarket.git /tmp/AliceMarket
mkdir -p .claude/skills
cp -r /tmp/AliceMarket/skills/moat_strength_review_skill .claude/skills/moat_strength_review_skill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Moat Strength Review Skill 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 Moat Strength Review Skill 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 Moat Strength Review Skill 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.

Moat Strength Review Skill

数据依赖与执行前置条件

推荐使用万得 wind-mcp-skill 获取底层数据。执行前先检查本地是否已有 wind-mcp-skill;若没有,提示用户安装:

bash
# GitHub
npx skills add Wind-Information-Co-Ltd/wind-skills --skill wind-mcp-skill -g -y

# Gitee 镜像(国内)
npx skills add https://gitee.com/wind_info/wind-skills.git --skill wind-mcp-skill -g -y

技能定位

本技能用于判断一家公司是否具备可持续竞争优势,以及这种优势是否足够深、足够稳、足够能转化为长期回报。输出重点不是给公司贴“好公司”标签,而是拆清护城河来自哪里、证据是否扎实、在什么情况下会被削弱。

执行流程

Step 1:明确要验证的护城河命题

先把“护城河”说具体。常见命题包括:

  • 成本优势是否足以长期压制同行
  • 品牌、渠道或客户关系是否形成进入门槛
  • 技术、专利、标准或生态是否构成锁定
  • 网络效应、规模效应或牌照资源是否具备持续性

如果只是短期领先而非结构性优势,应避免直接定义为护城河。

Step 2:识别优势来源与作用机制

逐项拆解公司竞争优势的来源,并说明其作用路径:

  • 它究竟如何帮助公司获取客户、维持价格、提高利润率或稳住份额
  • 它影响的是收入端、成本端还是资本回报端
  • 这种优势是行业共性,还是公司特有

这一阶段要把“听起来很强”转化为“如何产生经济结果”。

Step 3:寻找可验证证据

围绕竞争优势搜集可验证的证据,例如:

  • 市场份额与份额变化
  • 毛利率、费用率、回报率等长期表现
  • 客户粘性、复购率、切换成本或渠道掌控力
  • 行业内对手结构与进入难度

重点不是证据越多越好,而是证据是否能证明优势真实存在并持续发挥作用。

Step 4:评估持续性与削弱力量

分析护城河能否持续,重点观察:

  • 技术替代与商业模式替代风险
  • 监管与政策变化
  • 上下游议价结构改变
  • 新进入者、跨界者或价格战冲击

只有经得起反向审视的优势,才值得被视为长期护城河。

Step 5:判断优势是否能转化为股东回报

即使有竞争优势,也不一定意味着投资回报好。要进一步判断:

  • 优势是否体现为更高利润率或更稳回报
  • 管理层是否能把优势转化为合理资本配置
  • 当前估值是否已过度透支这份优势

这一步帮助区分“好公司”和“好股票”。

Step 6:给出护城河等级与跟踪信号

最终输出应回答:

  • 护城河强还是弱
  • 证据扎实还是偏叙事
  • 未来最重要的强化信号与削弱信号是什么

输出结构


{股票名称}护城河评估({YYYY-MM-DD})

一、结论摘要

  • 护城河等级:{强 / 中 / 弱 / 暂不成立}
  • 核心优势来源:{一句话}
  • 最大削弱风险:{一句话}

二、护城河命题

{用一段话明确当前要验证的竞争优势命题}

三、证据矩阵

优势类型证据当前判断说明
{类型1}{证据}{成立/部分成立/不足}{说明}
{类型2}{证据}{成立/部分成立/不足}{说明}

四、持续性分析

有利于持续的因素

  • {因素 1}
  • {因素 2}

可能削弱的力量

  • {风险 1}
  • {风险 2}

五、对投资的意义

  • 对经营质量的影响:{说明}
  • 对回报率的影响:{说明}
  • 对估值的影响:{说明}

六、后续跟踪信号

  • 强化信号:{信号}
  • 削弱信号:{信号}
  • 需要继续验证的问题:{问题}

质量要求

  1. 护城河必须落到可验证证据,不能停留在口号和想象。
  2. 要区分短期领先与结构性优势,不能把阶段景气当壁垒。
  3. 必须同时写清增强因素与削弱因素,防止单边美化。
  4. 最终结论要说明对投资回报的意义,而不是只评价公司“好不好”。
  5. 若证据不足,应明确写“尚不能证明护城河成立”。

Frequently asked questions

What does the Moat Strength Review Skill AI skill do?

评估公司竞争优势的来源、强度、可持续性与削弱风险,判断护城河是否真实存在并能转化为回报。适用于长线票初筛、优质公司研究、竞争壁垒判断等场景。

Why use Moat Strength Review Skill on TypingMind?

Because you install it once and use it with any model. Moat Strength Review Skill 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 Moat Strength Review Skill in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Wind-Alice/AliceMarket/tree/main/skills/moat_strength_review_skill. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Moat Strength Review Skill?

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 Moat Strength Review Skill?

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

Is the Moat Strength Review Skill AI skill free?

It is published on GitHub by Wind-Alice. 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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