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 kangarooking/duan-yongping-skill --skill stop-doing-listgit clone --depth 1 https://github.com/kangarooking/duan-yongping-skillWrote 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/kangarooking/duan-yongping-skill/stop-doing-list)<a href="https://agentmods.dev/skills/kangarooking/duan-yongping-skill/stop-doing-list"><img src="https://agentmods.dev/badge/skills/kangarooking/duan-yongping-skill/stop-doing-list/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/kangarooking/duan-yongping-skill/stop-doing-list"><img src="https://agentmods.dev/badge/skills/kangarooking/duan-yongping-skill/stop-doing-list.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 | $0.00123 | $0.02056 |
| Opus 5 | $0.00062 | $0.01028 |
| Sonnet 5 | $0.00025 | $0.00411 |
| Haiku 4.5 | $0.00012 | $0.00206 |
Grade A, and why
stop-doing-list 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 9d 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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Stop Doing List — 不为清单构建法
R — 原文 (Reading)
"好的公司都一定是有一个长长的'Stop doing list'，就是'不做的事情'。秘诀不是做了什么而是不做什么。"
— 段永平, 第7节
"发现是错的事情的时候要马上停止，不管多大的代价都是最小的代价。"
— 段永平, 第3节
I — 方法论骨架 (Interpretation)
Stop Doing List 是一套通过"不做什么"来定义"做什么"的逆向战略框架。它不是消极的回避，而是主动的战略排除。
核心逻辑：
- 两类不做：普世禁忌（谁都不该做的，如欺骗）+ 使命绑定（与公司愿景冲突的，如破坏品牌的事）
- 纠错机制：发现错了立刻停，此时代价永远最小——沉没成本不是继续的理由
- 累积效应：坚持10-20年，与不做清单的对手差距会巨大
- 建构方法：每条不做的背后都有故事、道理和逻辑，不是拍脑袋列的
段永平体系的具体条目（作为参考模板）：不讨价还价、不做代工、不借钱、不赊账、不拖付货款、不晚发工资、不做不诚信的事、不攻击竞争对手、不打价格战、不追求性价比、不做没差异化的产品、不弯道超车、不盲目扩张、不赚快钱、不虚夸产品。
A1 — 书中的应用 (Past Application)
案例 1: 步步高拒绝OEM订单
- 问题: 沃尔玛下100万台VCD的OEM订单，利润丰厚
- 方法论的使用: 段永平问"10年20年后回头看，做OEM对我们建立品牌有帮助吗？"答案是没有——资源会被分散
- 结论: 拒绝订单，全力做自有品牌
- 结果: 后续OPPO/vivo成为全球前五手机品牌，而同期做OEM的公司大多消失
案例 2: OPPO退出豆浆机市场
- 问题: OPPO做过豆浆机，发现方向不对
- 方法论的使用: 发现错了→立刻停，几亿损失在所不惜
- 结论: 退出豆浆机，聚焦手机
- 结果: 聚焦后OPPO成为全球前列手机品牌
案例 3: 统一价格、不设销售部
- 问题: 行业惯例是大客户谈折扣、小客户全价
- 方法论的使用: 把"不讨价还价"列入Stop Doing List
- 结论: 所有客户一个价，省掉整个销售部门和议价成本
- 结果: OPPO/vivo年收入合计400亿美金，没有Sales部门
A2 — 触发场景 (Future Trigger) ★
用户会在什么情境下需要这个 skill?
- 用户在制定公司战略或个人计划，列出了一堆想做的事但缺乏筛选标准
- 用户的公司发展太快，担心失控或犯致命错误
- 用户面临一个"看起来很好但有隐忧"的机会，在犹豫要不要做
- 用户反复犯同一类错误，想要一个系统性的纠错机制
- 用户在思考"为什么有些公司能基业长青而有些昙花一现"
语言信号 (用户的话里出现这些就应激活)
- "机会很多，不知道怎么选"
- "什么都想试试"
- "发展太快了有点担心"
- "怎么避免踩坑/翻车"
- "为什么有些公司能活很久"
- "我们犯了一个错误但已经投入了很多"
- "该不该做XX？"
与相邻 skill 的区分
- 与
right-things-first的区别: right-things-first 是"判断方向对不对"的底层哲学，stop-doing-list 是将其操作化为具体清单的执行工具 - 与
business-model-evaluator的区别: business-model-evaluator 评估商业模式好坏，stop-doing-list 列出"与好模式冲突的事绝不做"
E — 可执行步骤 (Execution)
当 skill 被激活后, agent 应按以下步骤执行:
-
帮助用户建立两类Stop Doing List
- 完成标准: 列出至少3条普世禁忌 + 至少3条使命绑定的条目
- 每条必须能用一句话说清"为什么不做"背后的逻辑
-
对每条进行"10年回头看"验证
- 完成标准: 对每条自问"10年后回头看，坚持不做是对的吗？"
- 判停条件: 如果任何一条在10年视角下站不住脚，重新审视其是否应该列入
-
建立纠错机制
- 完成标准: 明确"发现错了怎么停"的具体步骤——谁有权叫停、什么时候叫停、叫停后的善后流程
- 关键原则: 不管多大代价都是最小代价
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 151 lines · 123 tokens per session scan A bccb61969c4c
stop-doing-list is a skill published in the GitHub repository kangarooking/duan-yongping-skill (48 stars, last pushed 4mo ago), licensed MIT. It adds 123 tokens to every session and 2,056 once invoked, about $0.0006 per session on Opus 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 2026-08-30.
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