failed_breakout_exit_skill

failed_breakout_exit_skill is a skill for Claude Code, Codex from chuancyzhang/deepseek-cowork. It costs 64 tokens per session (1,356 once invoked), scanned A, original, Apache-2.0.

A guide to recognizing when a stock’s move above an important price level fails, reverses, or loses that level.

In plain words
What is it for?
Use it to decide when to reduce a position, set a loss limit, or put a failed trade back on the watchlist.
Why use it?
It helps traders respond to false breakouts and weakening momentum with a defined order of actions.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to decide when to reduce a position, set a loss limit, or put a failed trade back on the watchlist.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/chuancyzhang/deepseek-cowork/failed_breakout_exit_skill
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add chuancyzhang/deepseek-cowork --skill failed_breakout_exit_skill
Clone the repo
git clone --depth 1 https://github.com/chuancyzhang/deepseek-cowork

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for failed_breakout_exit_skill

README.md
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Your own site
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<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/failed_breakout_exit_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/failed_breakout_exit_skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,356 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00064 $0.01356
Opus 5.5 $0.00026 $0.00542
Sonnet 5.5 $0.00013 $0.00271
Haiku 4.5 $0.00006 $0.00136

Measured 1mo ago against content hash 8b7684c6bd4e, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

failed_breakout_exit_skill scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

ai_skills/wind-aifinmarket/skills/failed_breakout_exit_skill/SKILL.md · 143 lines

What it actually says

Failed Breakout Exit 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:

Cowork 适配:所需子 Skill 已随 wind-aifinmarket 固定快照内置,不执行安装或在线更新命令。

技能定位

本技能用于处理突破交易中最致命也最常见的失败场景: 价格站上去了,但承接没有跟上,随后回落失守关键位。输出重点不是解释为什么看错,而是帮助使用者尽快识别假突破、收缩风险暴露,并保留再次观察的秩序。

功能简介

本技能的核心功能是:识别假突破并给出撤退动作。

它强调把失败信号、撤退顺序和后续重评条件写清楚,帮助使用者在突破失效时快速修正,而不是抱着“可能再拉回去”的幻想拖延。

使用场景

  • 突破交易买入后,价格重新跌回关键位附近。
  • 盘中放量冲高但尾盘回落,用户不确定该不该立刻处理。
  • 次日低开失守使突破逻辑明显受损,需要快速修正。
  • 团队想把假突破退出机制写成标准化纪律。

工作原则

  1. 假突破的核心不是“跌了多少”,而是“突破前提是否被破坏”。
  2. 失败撤退必须优先处理风险,再处理情绪和解释。
  3. 需要区分正常回踩确认和真正的失效回落。
  4. 撤退后要保留重新观察条件,避免把纠错变成情绪报复。
  5. 正文只给出识别与动作框架,不讨论内部实现过程。

执行流程

Step 1:确认突破原始前提

先回到交易最初的成立条件:

  • 当时突破依赖的关键位、量能和环境是什么
  • 当前价格回落破坏的是哪一部分前提
  • 这笔交易原本属于试错突破还是确认突破
  • 是否仍存在合理的回踩确认解释空间

Step 2:识别假突破信号层级

把失败迹象分成不同严重度:

  • 盘中冲高回落但收盘仍站在关键位之上
  • 收盘跌回关键位下方
  • 次日低开继续走弱
  • 放量冲高后几乎无承接,形成明显抛压

不同层级对应的动作强度应不同。

Step 3:区分正常回踩与失败回落

避免把所有回踩都当作失败,但也不能自我安慰:

  • 回踩是否有缩量、承接和快速修复
  • 跌回关键位下方后能否迅速重新站回
  • 板块和环境是否仍支持再次发起
  • 若量价结构明显转差,是否已不再值得等待

Step 4:设计撤退动作顺序

一旦确认失败风险上升,应明确动作优先级:

  • 是先减半还是一次性退出
  • 若尾盘确认失效,是否应隔夜降低暴露
  • 若次日低开进一步失守,是否直接执行剩余退出
  • 是否保留极小观察仓,还是全部清空等待重建

Step 5:补充失败后的重评条件

失败处理不等于永远拉黑,需要写清楚什么情况下还能再看:

  • 重新站回关键位并得到承接
  • 板块重新强化
  • 出现新的催化或更优结构
  • 成交结构重新改善

Step 6:形成假突破撤退成稿

最终输出应帮助使用者知道“现在是噪音、回踩还是失败;如果是失败,该怎么退;退完以后什么时候再看”。正文保留信号分级、撤退顺序和重评条件。

输出结构


假突破撤退方案({YYYY-MM-DD})

一、30 秒结论

  • 交易对象:{股票名称}
  • 当前状态:{正常回踩 / 高风险 / 已确认失败}
  • 处理倾向:{继续观察 / 先降仓 / 明确退出}
  • 关键失效信号:{一句话}
  • 是否保留再观察资格:{是 / 否}

二、失败信号分级

层级 现象 含义 建议动作
轻度 {内容} {内容} {内容}
中度 {内容} {内容} {内容}
重度 {内容} {内容} {内容}

三、撤退动作顺序

  • {动作1}
  • {动作2}
  • {动作3}

四、重新观察条件

  • {条件1}
  • {条件2}
  • {条件3}

五、风险提示

  • {风险1}
  • {风险2}
  • {风险3}

质量要求

  1. 必须区分正常回踩与失败回落。
  2. 要对失败信号做层级划分,而不是只有二元判断。
  3. 撤退动作必须按顺序写清。
  4. 重新观察条件要具体,避免情绪性反复进出。
  5. 输出应帮助快速纠错,而不是延长侥幸期。
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 143 lines · 64 tokens per session scan A 8b7684c6bd4e

Subscribe to this mod's changes

failed_breakout_exit_skill is a skill published in the GitHub repository chuancyzhang/deepseek-cowork (18 stars, last pushed today), licensed Apache-2.0. It adds 64 tokens to every session and 1,356 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.

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