段永平长期检查

v2.0.0

[何时使用]当用户需要判断公司是否值得长期持有时;当用户问"这家公司能持有 10 年吗"时;当进行长期投资分析时;当应用段永平 10 年测试时

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Prompt PreviewInstall & Setup
Install the skill "段永平长期检查" (lj22503/duan-longterm) from ClawHub.
Skill page: https://clawhub.ai/lj22503/duan-longterm
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

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openclaw skills install duan-longterm

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npx clawhub@latest install duan-longterm
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Benign
high confidence
Purpose & Capability
Name/description (10-year hold test) match the included files: SKILL.md describes the checklist and templates, and scripts/check-longterm.py implements a local scoring tool. No unrelated capabilities or credentials are requested.
Instruction Scope
SKILL.md and templates only instruct the agent to apply the 10-year checklist and produce recommendations. There are no instructions to read unrelated files, access environment variables, or transmit data to external endpoints.
Install Mechanism
No install spec; skill is instruction-only with a small local Python script. Nothing is downloaded or written to disk by an installer. Risk from installation is minimal.
Credentials
No environment variables, credentials, or config paths are required. The skill does not request secrets or unrelated service access—requirements are proportionate to its stated purpose.
Persistence & Privilege
always is false and the skill does not request persistent system privileges or modify other skills. Autonomous invocation is allowed (platform default) but not combined with other risky behaviors.
Assessment
This skill appears coherent and low-risk: it contains a self-contained checklist and a local Python script that performs scoring without network access or credential use. Before installing, be aware: (1) it expresses an investment framework and is not financial advice; verify assumptions and scoring logic for your use case (the script defaults to neutral scores if no user input is provided); (2) the skill is Chinese-language—ensure that matches your workflow; (3) if you plan to feed sensitive data into the skill, confirm your agent's runtime doesn't log or transmit data elsewhere (the included code has no network calls). If you need stronger guarantees, inspect or run the Python script in a sandbox first.

Like a lobster shell, security has layers — review code before you run it.

10yearvk97b0f1y8q23sr55p48yy5t221838ypmholdingvk97b0f1y8q23sr55p48yy5t221838ypmlatestvk97b0f1y8q23sr55p48yy5t221838ypmlong-termvk97b0f1y8q23sr55p48yy5t221838ypm
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Updated 1mo ago
v2.0.0
MIT-0

段永平长期主义检查 ⏰

基于段永平 - "买入并持有 10 年+"


📋 功能描述

判断一家公司是否值得长期持有 10 年以上。

适用场景:

  • 长期投资价值判断
  • 10 年测试
  • 行业前景分析
  • 竞争优势持续性分析

边界条件:

  • 不替代深入研究
  • 预测有不确定性
  • 需定期复盘

🎯 10 年测试(5 个问题)

1. 10 年后这家公司会更大更强吗?

  • 行业增长空间
  • 公司竞争优势
  • 管理层能力

2. 10 年后行业还在吗?会更好吗?

  • 行业是否会被颠覆
  • 技术变革风险
  • 政策风险

3. 你愿意持有 10 年不卖出吗?

  • 即使股价下跌 50%
  • 即使市场恐慌
  • 即使有更好的短期机会

4. 10 年后竞争格局会如何?

  • 集中度提升
  • 公司地位稳固
  • 进入壁垒高

5. 10 年后股东回报如何?

  • 持续分红
  • 股票回购
  • 价值增长

通过标准: 5 个问题都回答"是"


⚠️ 常见错误

错误 1:过度自信预测

问题:
• 过度自信预测未来
• 忽视不确定性
• 忽视黑天鹅

解决:
✓ 保守预测
✓ 考虑多种情景
✓ 保持谦逊

错误 2:忽视技术变革

问题:
• 忽视技术颠覆风险
• 忽视行业变化
• 过度依赖历史

解决:
✓ 关注技术趋势
✓ 关注行业变化
✓ 定期复盘

错误 3:短期思维

问题:
• 被短期波动影响
• 忽视长期价值
• 频繁交易

解决:
✓ 关注长期价值
✓ 忽视短期波动
✓ 长期持有

🧪 使用示例

示例:苹果公司 10 年测试

输入:

公司:苹果
行业:消费电子
竞争优势:品牌 + 生态

输出:

1. 10 年后更大更强?✅ 是(生态扩张)
2. 行业还在吗?✅ 是(会更好)
3. 愿意持有 10 年?✅ 是
4. 竞争格局?✅ 集中度提升
5. 股东回报?✅ 持续回购

通过:5/5 ✅

建议:长期持有

📚 核心理念

关键洞察:

  1. 买入并持有 10 年+
  2. 好公司值得长期持有
  3. 忽视短期波动
  4. 关注长期价值
  5. 复利思维

健康公式:

长期价值 = 好公司 × 好价格 × 时间

更新日志

  • v2.0.0 (2026-03-19): 按照 SKILL-STANDARD-v2.md 重构,添加 Front Matter、坑点章节 ⏰
  • v1.0.0 (2026-03-13): 初始版本,段永平长期主义检查上线 ⏰

买入并持有 10 年+。好公司值得长期持有。

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