Theme Heat Tracker Skill

Organization

Wind-Alice

theme_heat_tracker_skill

跟踪主题题材的热度变化、扩散层级、拥挤程度与持续性，帮助判断题材处于启动、强化、扩散还是退潮阶段。适用于题材跟踪、热点复盘与轮动研判。

Overview

Publisher	Wind-Alice
Repository	`AliceMarket`
Skill name	`theme_heat_tracker_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 Theme Heat Tracker 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/theme_heat_tracker_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/theme_heat_tracker_skill .claude/skills/theme_heat_tracker_skill

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

Use it in TypingMind

Enable Theme Heat Tracker 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 Theme Heat Tracker 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 Theme Heat Tracker 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.

Theme Heat Tracker 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

本技能用于跟踪某一主题题材的热度变化，回答“这条题材现在热不热、热度来自哪里、是龙头驱动还是全面扩散、是否已经开始拥挤或退潮”。输出重点不是简单罗列相关新闻，而是帮助使用者判断题材所处阶段，以及应继续跟踪、择机参与还是降低关注。

执行流程

Step 1：界定题材边界与观察周期

先明确本次要跟踪的主题是什么，并把边界定义清楚：

题材名称对应的核心叙事是什么
哪些公司属于核心受益，哪些只是边缘映射
是观察单一题材，还是比较多个相近题材
是看日内热度、周度热度，还是阶段性热度演化

若题材边界模糊，应先做核心名单与边缘名单的区分，避免把无关标的混入热度判断。

Step 2：建立题材热度的多维观察框架

热度不应只看价格涨跌，需要从多个维度综合判断：

题材核心标的与跟随标的的表现强弱
题材内部上涨家数、持续性和梯队完整度
成交活跃度是否同步上升
新闻、政策、产业动态是否持续提供新催化
市场讨论热度是否集中且不断强化

这一阶段的目标是确认热度是否真实存在，而不是仅凭少数龙头表现下结论。

Step 3：判断题材所处阶段

结合市场表现和信息流变化，判断题材当前更接近哪一阶段：

启动阶段：少数先行标的率先异动，市场开始形成关注
强化阶段：核心标的持续走强，逻辑得到重复验证
扩散阶段：中军、二线、边缘映射标的普遍受益
拥挤阶段：交易过热、分支泛化、兑现压力升高
退潮阶段：题材热度减弱，仅剩个别强股维持表现

阶段判断必须有清晰依据，不能只使用情绪化表述。

Step 4：识别热度来源与延续条件

进一步说明题材之所以热，是因为什么，以及要继续热下去还需要什么条件：

是政策刺激、产业进展、业绩兑现还是市场风格配合
当前催化是一次性事件，还是可连续验证的主线
热度是否已经从叙事走向业绩支持
若后续没有新增催化，热度是否容易快速回落

Step 5：判断拥挤度与风险释放可能

热题材常见问题不是“有没有逻辑”，而是“是不是已经太拥挤”。重点说明：

核心标的是否已有明显抢跑
边缘标的是否被过度外延
题材涨幅和成交是否出现脱离基本逻辑的扩张
一旦情绪回落，最先承压的环节会在哪里

Step 6：形成题材热度跟踪成稿

最终输出应帮助使用者快速判断题材是值得继续跟踪、等待分歧、做高低切换，还是暂时回避。正文只保留阶段判断、驱动解释、拥挤风险与后续观察点。

输出结构

{题材名称}热度追踪（{YYYY-MM-DD}）

一、30 秒结论

当前热度水平：{高 / 中 / 低}
所处阶段：{启动 / 强化 / 扩散 / 拥挤 / 退潮}
热度来源：{一句话}
当前建议：{继续跟踪 / 优先看核心 / 防拥挤 / 暂不追高}

二、题材范围界定

核心逻辑：{内容}
核心标的：{内容}
边缘映射标的：{内容}

三、热度观察面板

维度	当前状态	判断
核心标的强度	{内容}	{判断}
跟随标的扩散	{内容}	{判断}
成交活跃度	{内容}	{判断}
新催化供给	{内容}	{判断}
市场讨论度	{内容}	{判断}

四、热度驱动与延续条件

当前最强驱动：{内容}
还能继续强化的条件：{内容}
最容易失速的原因：{内容}

五、拥挤度与风险提示

拥挤迹象：{内容}
最先可能退潮的环节：{内容}
需要回避的误判：{内容}

六、后续观察清单

{观察点 1}
{观察点 2}
{观察点 3}

质量要求

题材热度分析必须把“价格表现、扩散层级、催化供给、拥挤程度”放在同一框架下。
必须区分核心受益和边缘映射，避免题材外延无限扩大。
阶段判断应基于证据，不可仅凭情绪化词语。
需要同时写出延续条件和退潮风险，避免只给单边结论。
输出要能服务热点跟踪和轮动判断，而不是简单热点摘要。

Frequently asked questions

What does the Theme Heat Tracker Skill AI skill do?

Why use Theme Heat Tracker Skill on TypingMind?

Because you install it once and use it with any model. Theme Heat Tracker 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 Theme Heat Tracker Skill in TypingMind?

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

Which AI models can use Theme Heat Tracker 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 Theme Heat Tracker Skill?

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

Is the Theme Heat Tracker 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Theme Heat Tracker Skill

数据依赖与执行前置条件

技能定位

执行流程

Step 1：界定题材边界与观察周期

Step 2：建立题材热度的多维观察框架

Step 3：判断题材所处阶段

Step 4：识别热度来源与延续条件

Step 5：判断拥挤度与风险释放可能

Step 6：形成题材热度跟踪成稿

输出结构

{题材名称}热度追踪（{YYYY-MM-DD}）

一、30 秒结论

二、题材范围界定

三、热度观察面板

四、热度驱动与延续条件

五、拥挤度与风险提示

六、后续观察清单

质量要求

Frequently asked questions

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