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.
npx skills add chuancyzhang/deepseek-cowork --skill stop_loss_discipline_skillgit clone --depth 1 https://github.com/chuancyzhang/deepseek-coworkWrote 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.
[](https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/stop_loss_discipline_skill)<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/stop_loss_discipline_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/stop_loss_discipline_skill/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/stop_loss_discipline_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/stop_loss_discipline_skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00062 | $0.01479 |
| Opus 5.5 | $0.00025 | $0.00592 |
| Sonnet 5.5 | $0.00012 | $0.00296 |
| Haiku 4.5 | $0.00006 | $0.00148 |
Grade A, and why
stop_loss_discipline_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.
How it starts
The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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：
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。
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.
- 1mo ago First seen · 150 lines · 62 tokens per session scan A 8164ce71cc98
stop_loss_discipline_skill is a skill published in the GitHub repository chuancyzhang/deepseek-cowork (18 stars, last pushed today), licensed Apache-2.0. It adds 62 tokens to every session and 1,479 once invoked, about $0.0002 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.
Other skills, from other repositories
sector-rotation
An analysis framework for comparing industries in the Chinese A-share stock market, using business conditions, price momentum, valuation, and money flows. It produces rankings and higher- or lower-allocation suggestions.
twitter-reader
Read Twitter/X for financial research through opencli: the user's home timeline, tweet search, trending topics, bookmarks, a user's recent tweets, threads, articles, profiles, followers and following, and notifications. Use this skill whenever the user wants to know what people are saying on Twitter/X or fintwit about…
strategy-pivot-designer
Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.
energy-procurement
Codified expertise for electricity and gas procurement, tariff optimization, demand charge management, renewable PPA evaluation, and multi-facility energy cost management. Informed by energy procurement managers with 15+ years experience at large commercial and industrial consumers. Includes market structure analysis…
airdrop-hunting-guide
Guide to finding and qualifying for crypto airdrops — eligibility criteria, farming strategies, on-chain activity requirements, Sybil detection avoidance, and tracking tools. Use when helping users understand airdrops, check eligibility, or plan participation strategies.
recipe-daily-pnl-report
Generate a daily profit and loss summary from trades and balances.