Northbound Capital Flow Skill

Organization

Wind-Alice

northbound_capital_flow_skill

追踪北向资金或外资偏好的变化、行业流向与风格迁移，帮助判断资金面支持、抱团方向与潜在反转线索。适用于A股资金观察、风格判断与板块验证。

Overview

Publisher	Wind-Alice
Repository	`AliceMarket`
Skill name	`northbound_capital_flow_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 Northbound Capital Flow 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/northbound_capital_flow_skill
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/Wind-Alice/AliceMarket/tree/main/skills/northbound_capital_flow_skill

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

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/northbound_capital_flow_skill .claude/skills/northbound_capital_flow_skill

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

Use it in TypingMind

Enable Northbound Capital Flow 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 Northbound Capital Flow 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 Northbound Capital Flow 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.

Northbound Capital Flow 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

本技能用于跟踪北向资金或外资风格变化，回答“外资最近在买什么、卖什么、偏好有没有切换、这些流向是否支持当前市场主线”。输出重点不是简单罗列净流入净流出数字，而是解释资金偏好、行业迁移和与市场结构之间的关系。

执行流程

Step 1：确认观察周期、市场范围与比较基准

先明确本次资金分析的尺度：

是看单日、周度、月度还是阶段性变化
观察的是总体资金流，还是聚焦某一行业或股票池
需要与指数表现、板块轮动还是个股走势做对照
用户是想看当前风向，还是寻找趋势反转线索

若用户未说明，默认按“近期一周与一月”两个层次展开。

Step 2：梳理总体资金方向

先从总体上回答：

资金是在持续净流入、持续净流出，还是反复摇摆
资金行为更像配置型增配，还是交易型短线切换
当前流向与市场整体表现是否一致
资金拐点是否已经出现，还是仍在延续原趋势

这一阶段的目标是先建立大方向，而不是直接跳到细分板块。

Step 3：拆解行业与风格偏好

在总体方向明确后，进一步分析：

哪些行业或主题获得明显增配
哪些方向被持续减配
资金更偏好大盘龙头、成长风格、价值风格还是防御方向
风格迁移是否与市场轮动和宏观预期相吻合

Step 4：分析代表性标的与集中度

进一步判断流向是否集中在少数核心标的，重点包括：

资金是否高度抱团于少数权重或龙头
净流入是否具有板块层面的广泛性
某些个股的流向是否只是阶段性交易行为
外资偏好是否在行业内部做高低切换

Step 5：判断资金信号的可信度与局限

资金流向常被过度解读，因此需要补充说明：

单日流向是否容易受被动调仓或事件扰动影响
阶段性流向与长期配置逻辑是否一致
资金流入流出是否真正改变了趋势判断
若资金方向与价格方向背离，哪一边更值得重视

Step 6：形成北向资金风向成稿

最终输出应帮助使用者看清资金面支持在哪里、信号强不强、是否足以验证当前风格判断。正文只保留总体方向、偏好拆解、代表性标的和可信度判断。

输出结构

北向资金风向观察（{YYYY-MM-DD}）

一、30 秒结论

总体方向：{净流入 / 净流出 / 摇摆}
主要偏好：{内容}
风格变化：{内容}
当前含义：{支持主线 / 结构切换 / 信号一般 / 需谨慎解读}

二、总体流向概览

维度	当前表现	判断
近阶段总体流向	{内容}	{判断}
与指数关系	{内容}	{判断}
与市场情绪关系	{内容}	{判断}

三、行业与风格偏好

明显增配方向：{内容}
明显减配方向：{内容}
风格偏好变化：{内容}

四、代表性标的与集中度

核心受益标的：{内容}
集中抱团迹象：{内容}
高低切换线索：{内容}

五、信号可信度判断

可信度较强的部分：{内容}
容易误读的部分：{内容}
与价格背离时的解释：{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

资金分析必须先看总体方向，再看行业与个股，避免一上来只盯个别热门股。
要区分配置型流向和交易型流向，提升解释质量。
必须把资金流向与价格表现、板块轮动结合判断，不能孤立解读。
需提示被动调仓、事件扰动等局限，防止把单日流向当成长期信号。
输出要能帮助使用者判断资金面是否支持当前主线和风格迁移。

Frequently asked questions

What does the Northbound Capital Flow Skill AI skill do?

追踪北向资金或外资偏好的变化、行业流向与风格迁移，帮助判断资金面支持、抱团方向与潜在反转线索。适用于A股资金观察、风格判断与板块验证。

Why use Northbound Capital Flow Skill on TypingMind?

Because you install it once and use it with any model. Northbound Capital Flow 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 Northbound Capital Flow Skill in TypingMind?

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

Which AI models can use Northbound Capital Flow 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 Northbound Capital Flow Skill?

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

Is the Northbound Capital Flow 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

Northbound Capital Flow Skill

数据依赖与执行前置条件

技能定位

执行流程

Step 1：确认观察周期、市场范围与比较基准

Step 2：梳理总体资金方向

Step 3：拆解行业与风格偏好

Step 4：分析代表性标的与集中度

Step 5：判断资金信号的可信度与局限

Step 6：形成北向资金风向成稿

输出结构

北向资金风向观察（{YYYY-MM-DD}）

一、30 秒结论

二、总体流向概览

三、行业与风格偏好

四、代表性标的与集中度

五、信号可信度判断

六、后续观察清单

质量要求

Frequently asked questions

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