Peer Comparison Decision Skill logo

Peer Comparison Decision Skill

Organization
Wind-Alice
peer_comparison_decision_skill

横向比较同业候选公司的业务质量、增长、盈利、估值与催化差异,并给出相对强弱结论。适用于候选股二选一、行业内优中选优、建立优先跟踪顺序等场景。

Overview

PublisherWind-Alice
RepositoryAliceMarket
Skill namepeer_comparison_decision_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 Peer Comparison Decision 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/peer_comparison_decision_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/peer_comparison_decision_skill .claude/skills/peer_comparison_decision_skill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Peer Comparison Decision 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 Peer Comparison Decision 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 Peer Comparison Decision 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.

Peer Comparison Decision 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

本技能用于在同一行业或同一主题内,对 2-5 家候选公司做横向比较,并输出可执行的相对排序与选择理由。重点不是把每家公司都重新写一遍,而是帮助使用者回答“如果只能优先研究或持有其中几家,应该先选谁、为什么”。

执行流程

Step 1:确认可比范围与比较目标

先明确比较对象是否真正可比,重点确认:

  • 所处赛道是否一致
  • 商业模式是否相近
  • 处于相似的发展阶段还是明显错位
  • 用户想比较的是短期交易机会还是中长期配置价值

若对象并不适合直接比较,应先说明可比性边界,再决定是否继续强行并列。

Step 2:建立统一比较框架

围绕用户真实决策,把比较维度标准化。常用维度包括:

  • 业务质量与竞争位置
  • 成长速度与成长确定性
  • 盈利能力与现金创造能力
  • 估值高低与预期要求
  • 近期催化与风险暴露

所有候选公司都按同一框架展开,避免某家公司只写故事、另一家公司只看数字。

Step 3:完成基础数据与事实对齐

收集每家公司的关键事实,并统一口径后放入对照表,特别注意:

  • 时间口径一致
  • 币种与单位一致
  • 估值方法口径一致
  • 对异常值和一次性因素进行说明

这一阶段的目标是把后续判断建立在同一坐标系之上。

Step 4:比较“业务质量”而不是只比较“数据高低”

除关键财务指标外,还要比较:

  • 核心产品与客户结构
  • 市场份额与竞争优势
  • 业务模式的抗波动能力
  • 管理执行与资本配置风格

若某家公司短期数据更亮眼,但业务稳定性明显更弱,应明确指出,不可被表面增速误导。

Step 5:比较“赔率”与“催化顺序”

真正的比选往往不只看谁更好,还要看谁更值得现在买入或优先跟踪。需重点判断:

  • 哪家公司好但已被充分定价
  • 哪家公司一般但预期差更大
  • 哪家公司短期有催化,哪家公司需要时间兑现
  • 哪家公司更适合观察,哪家公司更适合行动

Step 6:输出排序与决策建议

在完成横向比较后,给出明确排序,并说明:

  • 排名靠前的核心理由
  • 排名靠后的主要短板
  • 若只能研究一只、持有一只或短期交易一只,分别应如何选择

若结论取决于用户风格差异,也要明确把“成长型偏好”“价值型偏好”“交易型偏好”拆开说明。

输出结构


{行业/主题}同业比选({YYYY-MM-DD})

一、结论摘要

  • 最佳综合选择:{公司}
  • 最佳预期差选择:{公司}
  • 最适合继续观察:{公司}

二、统一比较表

公司业务定位增长盈利估值近期催化主要风险
{公司A}{描述}{描述}{描述}{描述}{描述}{描述}
{公司B}{描述}{描述}{描述}{描述}{描述}{描述}

三、相对强弱分析

业务质量

  • {谁更强,强在哪里}

成长质量

  • {谁更强,强在哪里}

估值赔率

  • {谁更有吸引力,原因是什么}

催化与时点

  • {谁更适合当下,原因是什么}

四、最终排序

排名公司结论
1{公司}{理由}
2{公司}{理由}
3{公司}{理由}

五、决策建议

  • 如果只能先研究一只:{公司},因为 {理由}
  • 如果只能先跟踪一只:{公司},因为 {理由}
  • 如果只能先规避一只:{公司},因为 {理由}

质量要求

  1. 只比较真正可比的对象,必要时先写清不可比之处。
  2. 统一使用同一比较口径,避免数据和叙事各说各话。
  3. 输出重点是“相对强弱与排序”,不是多篇个股介绍拼接。
  4. 必须同时比较质量、估值和时点,不能只用单一指标排名。
  5. 若结论明显依赖投资风格,应把适用人群写清楚。

Frequently asked questions

What does the Peer Comparison Decision Skill AI skill do?

横向比较同业候选公司的业务质量、增长、盈利、估值与催化差异,并给出相对强弱结论。适用于候选股二选一、行业内优中选优、建立优先跟踪顺序等场景。

Why use Peer Comparison Decision Skill on TypingMind?

Because you install it once and use it with any model. Peer Comparison Decision 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 Peer Comparison Decision Skill in TypingMind?

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

Which AI models can use Peer Comparison Decision 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 Peer Comparison Decision Skill?

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

Is the Peer Comparison Decision 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇