Growth Quality Check Skill

Organization

Wind-Alice

growth_quality_check_skill

拆解公司增长来源，检查其盈利含量、现金含量、可持续性与失速风险，判断增长是否“有质量”。适用于高成长股筛选、成长逻辑复核、景气股辨别真伪等场景。

Overview

Publisher	Wind-Alice
Repository	`AliceMarket`
Skill name	`growth_quality_check_skill`
Stars	135
Forks	18
Bundled files	Instructions only
Links	Skill source Repository Homepage

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 Growth Quality Check Skill AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/Wind-Alice/AliceMarket/tree/main/skills/growth_quality_check_skill
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.

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/growth_quality_check_skill .claude/skills/growth_quality_check_skill

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Growth Quality Check 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 Growth Quality Check 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 Growth Quality Check 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.

Growth Quality Check 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的增长是否值得信任。输出重点不是只看增速高低，而是拆解增长到底从哪里来、是否带来更好的利润和现金、是否具备可持续性，以及最容易在哪个环节失速。

执行流程

Step 1：确认要检验的增长命题

先明确当前市场在讨论哪一种增长：

收入高增长
利润高增长
某业务分部的结构性高增长
困境后恢复性增长

不同增长类型，判断标准不同，不能一套逻辑通用。

Step 2：拆解增长来源

把增长拆成可解释的来源，而不是停留在总量数字：

量增还是价增
老产品扩张还是新品贡献
内生增长还是并购并表
单一大客户拉动还是多客户普遍改善
景气顺风还是公司份额提升

这一步的目标是识别增长的质量与纯度。

Step 3：检验增长是否伴随盈利与现金改善

高质量增长通常不只体现在收入，还应观察：

利润率是否同步改善
费用投放是否失控
现金回款是否跟得上
库存、应收、资本开支是否异常拉升

若增长依赖激进让利、压货或大幅透支现金，应显著降级判断。

Step 4：判断增长的持续性

从持续性角度反推：

当前增长驱动能维持多久
未来一年是否仍有同样强的催化
是否存在高基数、需求前置、补贴退坡等问题
行业内供给变化会不会削弱增长质量

Step 5：识别最可能的失速路径

任何增长逻辑都要回答“最先可能坏在哪里”。重点关注：

单一产品周期见顶
大客户回落
竞争加剧导致价格回吐
景气拐点或政策变化

这一部分是为了区分“暂时很快”与“真正有持续性”。

Step 6：给出增长质量评级与跟踪框架

最终输出应回答：

这家公司增长质量高不高
高质量体现在哪些方面
接下来最该盯的验证指标是什么

输出结构

{股票名称}增长质检（{YYYY-MM-DD}）

一、结论摘要

增长质量评级：{高 / 中 / 低}
主要增长来源：{一句话}
最大失速风险：{一句话}

二、增长来源拆解

维度	当前情况	评价
量/价驱动	{描述}	{说明}
内生/外延	{描述}	{说明}
产品/客户结构	{描述}	{说明}
景气/份额驱动	{描述}	{说明}

三、盈利与现金含量

利润率表现：{说明}
现金含量：{说明}
潜在质量瑕疵：{说明}

四、持续性判断

{持续性支撑点 1}
{持续性支撑点 2}
{持续性约束点}

五、最可能的失速路径

{失速风险 1}
{失速风险 2}
{失速风险 3}

六、后续跟踪指标

最关键指标：{指标}
验证周期：{周期}
失效信号：{信号}

质量要求

高增长不等于高质量，必须拆解来源与代价。
不能只看收入增速，还要看利润和现金是否同步兑现。
要区分一次性拉动与可持续增长，避免线性外推。
风险部分要写最可能的失速路径，而不是泛泛提示“竞争激烈”。
最终结论应帮助判断增长值不值得付出更高估值。

Frequently asked questions

What does the Growth Quality Check Skill AI skill do?

Why use Growth Quality Check Skill on TypingMind?

Because you install it once and use it with any model. Growth Quality Check 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 Growth Quality Check Skill in TypingMind?

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

Which AI models can use Growth Quality Check 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 Growth Quality Check Skill?

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

Is the Growth Quality Check 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

Claw Score

openclaw

OrganizationPopular

Audit or refresh OpenClaw maturity scorecard docs from root taxonomy, maturity scores, and QA evidence artifacts without using maintainer discrawl data or committed inventory reports.

Clawsweeper

Use for all ClawSweeper work: OpenClaw issue/PR sweep reports, repair jobs, cloud fix PRs, @clawsweeper maintainer mention commands, trusted ClawSweeper-reviewed autofix/automerge, GitHub Actions…

Control Ui E2e

Use when designing, testing, fixing, or extending the OpenClaw Control UI GUI, including UI stress-test galleries with feedback inputs, Vitest + Playwright end-to-end checks, mocked Gateway flows,…

Deslop

Diff-scoped AI-slop cleanup pass: strip comment slop, defensive-check slop, type-laundering, and style drift from the current branch diff before autoreview.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Growth Quality Check Skill

数据依赖与执行前置条件

技能定位

执行流程

Step 1：确认要检验的增长命题

Step 2：拆解增长来源

Step 3：检验增长是否伴随盈利与现金改善

Step 4：判断增长的持续性

Step 5：识别最可能的失速路径

Step 6：给出增长质量评级与跟踪框架

输出结构

{股票名称}增长质检（{YYYY-MM-DD}）

一、结论摘要

二、增长来源拆解

三、盈利与现金含量

四、持续性判断

五、最可能的失速路径

六、后续跟踪指标

质量要求

Frequently asked questions

Related AI Skills

Set up your own AI workspace now