Earnings Preview Skill logo

Earnings Preview Skill

Organization
Wind-Alice
earnings_preview_skill

财报前梳理市场预期、关键看点、验证指标、情景推演与风险点。适用于财报发布前准备、会前讨论、盘前预案制定等场景。

Overview

PublisherWind-Alice
RepositoryAliceMarket
Skill nameearnings_preview_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 Earnings Preview 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/earnings_preview_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/earnings_preview_skill .claude/skills/earnings_preview_skill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Earnings Preview 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 Earnings Preview 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 Earnings Preview 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.

Earnings Preview 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

本技能用于在财报发布前,把“市场在等什么、公司最该证明什么、如果结果不同会怎样”整理成一份高密度前瞻底稿。输出重点不是泛泛罗列财务指标,而是帮助使用者在财报前明确预期基线、关键验证点、潜在预期差和会前应重点关注的问题。

执行流程

Step 1:确认分析对象、财报周期与使用目的

先确认股票名称、上市地、本次对应的财报周期,以及用户此时要解决的问题:

  • 是为了会前快速准备
  • 是为了判断是否值得参与财报交易
  • 是为了给团队做前瞻讨论底稿
  • 是为了在持仓前明确风险暴露

若用户未说明,默认按“财报公布前的研究准备”展开,并聚焦最近一次待发布财报。

Step 2:建立市场预期基线

先把市场已经形成的预期整理清楚,重点包括:

  • 收入、利润、利润率等核心指标的市场预期区间
  • 管理层上次给出的指引或暗示
  • 卖方与市场讨论最集中的关键经营变量
  • 上一季度财报后遗留的验证任务
  • 当前股价隐含的预期温度是保守、中性还是偏热

这一阶段的目标不是直接下结论,而是先明确“市场已经知道什么、已经押注什么、还在争论什么”。

Step 3:拆解本次财报最重要的验证点

围绕公司当前阶段,提炼 3-5 个真正决定财报解读方向的核心问题。优先关注:

  • 本季度业绩是否只是表面超预期,还是质量也同步改善
  • 增长来源是量、价、结构还是一次性因素
  • 利润率、费用率、现金流是否支持当前增长叙事
  • 订单、用户、产能、库存、开店、出货等经营变量是否验证主线
  • 管理层是否需要在本次财报中回应市场最大的疑虑

验证点必须足够具体,能够在财报正文、业绩会或后续公告里被验证,而不是宽泛口号。

Step 4:做情景推演与反应框架

在预期基线和关键变量明确后,对财报结果做条件化推演,至少覆盖:

  • 明显超预期时,真正的惊喜会来自哪里
  • 略超预期但股价不涨时,市场可能在担心什么
  • 表面达标但指引偏弱时,解读应如何调整
  • 若核心经营变量不及预期,市场会优先交易哪条风险链条
  • 哪些情况下需要把“好财报”和“好股票表现”区分开看

这一步的重点是把“结果”与“市场反应”拆开处理,避免把财报前瞻写成单向押注。

Step 5:形成会前关注清单

基于前述分析,整理出财报前最值得带着去看的问题,包括:

  • 财报发布后要先核对的三个数字
  • 业绩会最值得听的两个问题方向
  • 哪些措辞变化会明显改变判断
  • 哪些风险即使财报不错也不能忽略
  • 若结果模糊,应等待哪些补充信息再下结论

Step 6:整合成前瞻成稿

最终输出应是面向行动的前瞻底稿,不展示中间检索路径、信息收集过程或内部草稿。正文不需要解释信息如何获得,只需要呈现预期、分歧、推演和行动重点。

输出结构


{股票名称}财报前瞻({YYYY-MM-DD})

一、30 秒结论

  • 本次财报最重要的看点:{一句话}
  • 市场当前最关注的变量:{一句话}
  • 最容易出现预期差的地方:{一句话}
  • 财报前整体判断:{偏积极 / 中性等待 / 偏谨慎}

二、市场预期基线

维度当前预期说明
收入{数值或区间}{说明}
利润/EPS{数值或区间}{说明}
关键经营指标{数值或区间}{说明}
指引预期{上修 / 持平 / 下修预期}{说明}

三、本次最关键的验证点

  • 验证点 1:{内容}
  • 验证点 2:{内容}
  • 验证点 3:{内容}

四、情景推演

情景 A:明显超预期

  • 触发条件:{条件}
  • 可能反应:{判断}

情景 B:结果平稳但反应分化

  • 触发条件:{条件}
  • 可能反应:{判断}

情景 C:不及预期

  • 触发条件:{条件}
  • 可能反应:{判断}

五、财报前风险提示

  • {风险 1}
  • {风险 2}
  • {风险 3}

六、会前问题清单

  • {问题 1}
  • {问题 2}
  • {问题 3}

质量要求

  1. 前瞻必须围绕“预期差”展开,而不是重复公司背景资料。
  2. 关键看点应尽量具体到指标、业务模块或管理层表态方向。
  3. 要区分“财报结果好坏”和“股价反应强弱”这两个层次。
  4. 若市场预期并不清晰,应明确写出预期不一致,而不是强行给出单一口径。
  5. 文本要能直接服务财报前准备与会后验证,避免写成泛泛研究摘要。

Frequently asked questions

What does the Earnings Preview Skill AI skill do?

财报前梳理市场预期、关键看点、验证指标、情景推演与风险点。适用于财报发布前准备、会前讨论、盘前预案制定等场景。

Why use Earnings Preview Skill on TypingMind?

Because you install it once and use it with any model. Earnings Preview 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 Earnings Preview Skill in TypingMind?

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

Which AI models can use Earnings Preview 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 Earnings Preview Skill?

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

Is the Earnings Preview 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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