Stop Loss Discipline Skill

Organization

Wind-Alice

stop_loss_discipline_skill

为单笔交易设计价格止损、逻辑止损与时间止损规则，并给出触发后的执行动作与复核顺序。适用于下单前纪律设定、持仓修正与减少犹豫止损场景。

Overview

Publisher	Wind-Alice
Repository	`AliceMarket`
Skill name	`stop_loss_discipline_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 Stop Loss Discipline 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/stop_loss_discipline_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/stop_loss_discipline_skill .claude/skills/stop_loss_discipline_skill

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

Use it in TypingMind

Enable Stop Loss Discipline 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 Stop Loss Discipline 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 Stop Loss Discipline 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.

Stop Loss Discipline 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

本技能用于把“跌了再看”改造成“什么时候认错、怎么认错、认错后做什么”的纪律方案。输出重点不是鼓励机械式砍仓，而是帮助使用者提前设定清晰的退出触发器，减少持仓过程中最常见的拖延、侥幸和自我合理化。

功能简介

本技能的核心功能是：设计止损触发条件与执行动作。

它强调把价格失效、逻辑失效和时间失效同时纳入管理，帮助使用者在亏损早期就完成判断，而不是把交易错误拖成账户问题。

使用场景

用户想在下单前先把止损纪律写清楚。
持仓已经进入不利状态，但不确定是否应立即处理。
团队需要统一止损语言，减少盘中临时争论。
用户经常“知道该止损，但总是下不了手”。

工作原则

止损的本质是确认原计划失效，而不是单纯害怕亏损。
必须区分噪音波动与真正失效，避免把随机扰动当作计划终结。
止损纪律应覆盖价格、逻辑、时间三个维度。
触发后要有明确动作顺序，不能只写“考虑减仓”。
正文只输出纪律框架与执行建议，不描述内部实现过程。

执行流程

Step 1：确认原始交易计划与失效标准

任何止损设计都要回到原计划本身：

这笔交易最初是基于什么逻辑建立
哪个关键变量一旦被破坏，计划就不再成立
当前持仓属于试错阶段还是确认阶段
用户更担心价格波动，还是逻辑拖延

Step 2：设定价格止损边界

先给出最直观的价格纪律：

哪个关键支撑、平台或结构位不能有效跌破
是采用收盘确认、盘中失守，还是连续多日失效来认定
是否要考虑波动缓冲，避免被正常噪音轻易洗出
若标的波动天然较大，是否需要降低仓位而不是放宽纪律

Step 3：识别逻辑止损触发器

有些交易不是价格先错，而是理由先错。需要检查：

原本依赖的事件、业绩、资金、板块支持是否消失
市场分歧是否已朝不利方向收敛
关键催化剂是否被证伪或延后
持仓理由是否悄悄从“主动计划”变成“被动死扛”

Step 4：设置时间止损

如果交易长时间不朝计划方向演化，也应视为成本：

原本预期多快验证，现在是否已经明显拖延
横盘或弱势震荡是否占用了过多资金和注意力
当前时间成本是否使得更优机会被错过
到达时间阈值后，是全部退出还是先降仓再观察

Step 5：设计触发后的动作优先级

止损不是一个按钮，而是一套动作顺序：

是先减半、再观察，还是一次性退出
盘中触发后是否允许等待特定确认
若出现跳空失守，执行方式是否需要调整
止损后是否允许重新评估，还是必须等待新结构

Step 6：处理常见干扰因素

把最容易破坏纪律的情形提前写清：

板块暂时转弱但个股逻辑未坏
跌破后快速收回
连续小亏后产生“这次再等等”的冲动
因成本价锚定而拒绝执行客观规则

Step 7：形成止损纪律成稿

最终输出应帮助使用者知道“什么情况下必须动、怎么动、动完以后怎么复盘”。正文保留触发条件、动作顺序和例外处理原则。

输出结构

止损纪律方案（{YYYY-MM-DD}）

一、30 秒结论

持仓对象：{股票名称}
当前状态：{未入场 / 已入场 / 接近失效}
核心止损类型：{价格 / 逻辑 / 时间}
执行倾向：{严格执行 / 条件执行 / 继续观察}
最大风险点：{一句话}

二、止损框架

维度	触发条件	执行动作
价格止损	{内容}	{内容}
逻辑止损	{内容}	{内容}
时间止损	{内容}	{内容}

三、例外情形处理

常规噪音波动：{内容}
跳空失守：{内容}
跌破后快速收回：{内容}

四、止损后动作

{动作1}
{动作2}
{动作3}

五、纪律提醒

{提醒1}
{提醒2}
{提醒3}

质量要求

必须同时覆盖价格、逻辑和时间三个层面。
触发条件要尽量客观，不能只写“感觉走弱”。
要给出触发后的明确动作，而不是含糊建议。
若存在例外情形，必须说明适用边界。
输出应降低犹豫止损，而不是帮助拖延。

Frequently asked questions

What does the Stop Loss Discipline Skill AI skill do?

为单笔交易设计价格止损、逻辑止损与时间止损规则，并给出触发后的执行动作与复核顺序。适用于下单前纪律设定、持仓修正与减少犹豫止损场景。

Why use Stop Loss Discipline Skill on TypingMind?

Because you install it once and use it with any model. Stop Loss Discipline 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 Stop Loss Discipline Skill in TypingMind?

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

Which AI models can use Stop Loss Discipline 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 Stop Loss Discipline Skill?

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

Is the Stop Loss Discipline 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

Stop Loss Discipline Skill

数据依赖与执行前置条件

技能定位

功能简介

使用场景

工作原则

执行流程

Step 1：确认原始交易计划与失效标准

Step 2：设定价格止损边界

Step 3：识别逻辑止损触发器

Step 4：设置时间止损

Step 5：设计触发后的动作优先级

Step 6：处理常见干扰因素

Step 7：形成止损纪律成稿

输出结构

止损纪律方案（{YYYY-MM-DD}）

一、30 秒结论

二、止损框架

三、例外情形处理

四、止损后动作

五、纪律提醒

质量要求

Frequently asked questions

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