Institutional Position Shift Skill logo

Institutional Position Shift Skill

Organization
Wind-Alice
institutional_position_shift_skill

识别机构持仓变化、共识强化与调仓方向,帮助判断哪些公司或行业正在被增配、减配或重新定价。适用于13F、基金季报、机构持仓复盘与风格验证。

Overview

PublisherWind-Alice
RepositoryAliceMarket
Skill nameinstitutional_position_shift_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 Institutional Position Shift 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/institutional_position_shift_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/institutional_position_shift_skill .claude/skills/institutional_position_shift_skill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Institutional Position Shift 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 Institutional Position Shift 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 Institutional Position Shift 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.

Institutional Position Shift 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

本技能用于分析机构持仓变化,回答“哪些方向被机构明显增配或减配、这些变化体现了什么共识、是高信念加仓还是被动调整、对后续市场和个股意味着什么”。输出重点不是简单比较持股数量,而是解释持仓变化背后的偏好迁移和潜在影响。

执行流程

Step 1:确认样本范围、报告周期与解读口径

先明确本次研究的样本和边界:

  • 观察的是哪类机构
  • 覆盖的是单只股票、一个行业,还是更大的股票池
  • 对应的是哪个报告周期
  • 用户更关心机构共识变化,还是某几家核心机构的动作

同时要提醒使用者:机构持仓披露通常存在时间滞后,结论应结合这一点解读。

Step 2:梳理持仓变化的总体特征

先从整体上判断:

  • 哪些行业或风格被集中增配
  • 哪些方向被系统性减配
  • 机构持仓是更集中还是更分散
  • 原有热门方向是否仍在强化,还是开始松动

这一阶段的目标是先把大方向看清楚。

Step 3:拆解重点公司和代表性变化

进一步聚焦最有代表性的持仓变化:

  • 哪些公司被明显增持
  • 哪些公司被明显减持
  • 哪些变化来自原有核心仓位继续加码
  • 哪些变化体现机构从旧主线转向新主线

应优先挑选能代表共识变化的样本,而不是机械罗列全部名单。

Step 4:区分高信念调仓与被动变化

机构持仓变化并不都具有同样含义,需要进一步判断:

  • 是主动表达观点,还是被动因涨跌、基准调整或流动性原因而变化
  • 加仓是否伴随更高集中度
  • 减仓是否代表观点转弱,还是阶段性兑现
  • 是否存在机构之间分歧加大而非单一共识强化

Step 5:提炼对行业、主题与个股的含义

围绕调仓结果,说明:

  • 哪些行业或主题正在获得机构共识支持
  • 哪些公司可能因机构增持得到估值与流动性支撑
  • 哪些公司若出现机构撤退,风险应如何评估
  • 后续需要通过哪些经营或市场信号验证机构判断是否正确

Step 6:形成机构调仓洞察成稿

最终输出应帮助使用者理解机构共识在往哪里走,以及该如何看待这些披露信息。正文只保留持仓变化、偏好解读、局限说明和验证框架。

输出结构


机构调仓洞察({报告周期})

一、30 秒结论

  • 本期机构偏好方向:{内容}
  • 最明显的增配线索:{内容}
  • 最明显的减配线索:{内容}
  • 当前含义:{共识强化 / 分歧加大 / 结构切换}

二、总体持仓变化

维度当前表现判断
行业层面{内容}{判断}
风格层面{内容}{判断}
集中度变化{内容}{判断}

三、重点公司变化

  • 明显增持公司:{内容}
  • 明显减持公司:{内容}
  • 最具代表性的调仓动作:{内容}

四、调仓性质判断

  • 高信念主动调仓:{内容}
  • 可能的被动变化:{内容}
  • 机构分歧点:{内容}

五、市场含义与风险提示

  • 对行业/主题的含义:{内容}
  • 对个股的含义:{内容}
  • 解读局限:{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

  1. 机构持仓分析必须提醒披露滞后,避免把历史持仓直接当成当前动作。
  2. 要区分主动高信念调仓与被动变化,提升解释可信度。
  3. 需同时覆盖行业、风格和重点个股三个层次。
  4. 若机构之间分歧明显,应明确写出,而不是强行概括成一致共识。
  5. 输出要帮助使用者理解机构偏好迁移,而不是停留在持股名单罗列。

Frequently asked questions

What does the Institutional Position Shift Skill AI skill do?

识别机构持仓变化、共识强化与调仓方向,帮助判断哪些公司或行业正在被增配、减配或重新定价。适用于13F、基金季报、机构持仓复盘与风格验证。

Why use Institutional Position Shift Skill on TypingMind?

Because you install it once and use it with any model. Institutional Position Shift 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 Institutional Position Shift Skill in TypingMind?

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

Which AI models can use Institutional Position Shift 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 Institutional Position Shift Skill?

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

Is the Institutional Position Shift 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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