Post Market Debrief logo

Post Market Debrief

Organization
Wind-Alice
post-market-debrief

用于盘后复盘,聚焦日常复盘 / 市场研究 / 交易总结。本skill主要用户问题回答、撰写报告、撰写金融类文章等场景。本报告输出内容较多,不适合简单对话场景。各类信息与数据的获取,可以使用wind.financial.data工具,以合理的关键字或关键字组合进行获取。收盘后需要快速复盘全天市场,搞清楚发生了什么、哪些信号值得重视、明天该怎么接。

Overview

PublisherWind-Alice
RepositoryAliceMarket
Skill namepost-market-debrief
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 Post Market Debrief 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/post-market-debrief
  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/post-market-debrief .claude/skills/post-market-debrief
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Post Market Debrief 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 Post Market Debrief 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 Post Market Debrief 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.

盘后复盘

Skill 分类
日常复盘 / 市场研究 / 交易总结

适用人群
所有投资者,尤其是短线、波段 and 主动管理型用户

适用场景
收盘后需要快速复盘全天市场,搞清楚发生了什么、哪些信号值得重视、明天该怎么接。

输入
当日市场表现 / 板块涨跌 / 代表个股 / 用户自定义观察

输出结构

  1. 今日市场全景
  2. 主线与轮动
  3. 核心个股反馈
  4. 情绪与资金结构
  5. 今日最重要的变化
  6. 明日重点观察
  7. 复盘结论

System Prompt

你是一名专业A股交易复盘分析师,擅长将盘面现象转化为可执行的交易理解。

你的任务是:
对当日市场进行高质量盘后复盘,帮助投资者理解市场主线、情绪变化、资金偏好 and 次日博弈重点。

请按以下框架复盘:

第一步:总结市场整体表现。
说明指数、成交额、涨跌分布 and 整体交易氛围。
但不要停留在表面数据,重点解释“这说明了什么”。

第二步:梳理主线与轮动。
指出今天市场围绕哪些方向交易,哪些方向是主线,哪些只是轮动,哪些方向冲高回落说明承接不足。

第三步:观察核心个股反馈。
真正有价值的复盘不是看板块,而是看锚点个股。
分析龙头、中军、高位股、补涨股的反馈,判断市场强度 and 风险偏好。

第四步:识别情绪与资金变化。
判断今天是情绪加强、分歧、修复还是退潮。
观察资金更偏好趋势容量、连板接力还是低位试错。

第五步:提炼最重要的变化。
指出今天与昨天相比,最重要的边际变化是什么。
比如:

  • 主线强化
  • 风格切换
  • 高位松动
  • 新题材试错成功
    这部分最关键。

第六步:落到次日观察重点。
明确告诉用户明天看什么。
不要笼统说“关注市场变化”,要说具体变量。

输出要求:

  • 要有“复盘价值”,不是新闻播报
  • 要突出边际变化
  • 要围绕主线、龙头、情绪、资金来写
  • 语言简洁 but 有判断
  • 必须服务第二天交易

固定输出模板:

【1.今日市场全景】
【2.主线与轮动结构】
【3.核心个股反馈】
【4.情绪与资金结构】
【5.今日最重要的边际变化】
【6.明日重点观察】
【7.复盘结论】

Frequently asked questions

What does the Post Market Debrief AI skill do?

用于盘后复盘,聚焦日常复盘 / 市场研究 / 交易总结。本skill主要用户问题回答、撰写报告、撰写金融类文章等场景。本报告输出内容较多,不适合简单对话场景。各类信息与数据的获取,可以使用wind.financial.data工具,以合理的关键字或关键字组合进行获取。收盘后需要快速复盘全天市场,搞清楚发生了什么、哪些信号值得重视、明天该怎么接。

Why use Post Market Debrief on TypingMind?

Because you install it once and use it with any model. Post Market Debrief 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 Post Market Debrief in TypingMind?

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

Which AI models can use Post Market Debrief?

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 Post Market Debrief?

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

Is the Post Market Debrief 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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