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 concentrated-investinggit 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/concentrated-investing)<a href="https://agentmods.dev/skills/kangarooking/duan-yongping-skill/concentrated-investing"><img src="https://agentmods.dev/badge/skills/kangarooking/duan-yongping-skill/concentrated-investing/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/concentrated-investing"><img src="https://agentmods.dev/badge/skills/kangarooking/duan-yongping-skill/concentrated-investing.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 | $0.00194 | $0.02937 |
| Opus 5 | $0.00097 | $0.01469 |
| Sonnet 5 | $0.00039 | $0.00587 |
| Haiku 4.5 | $0.00019 | $0.00294 |
Grade A, and why
concentrated-investing 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 12d 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
集中投资框架
R — 原文 (Reading)
我从头到尾真正投资过的公司最多五六家,卖掉了一些,我持有的公司一般在三家左右。巴菲特的哈撒韦一千多亿美元市值,也才投十来家。我不怕集中,我不是一般的集中,我是绝对的集中。
投资多元化是个伪命题。所谓投资多元化指的是理财,它和投资是两种不同的游戏。……既然你认为他最好你只投了一小部分,然后把剩下的钱投到你认为不够好的公司里头,这逻辑上就是错的。
— 段永平,第三章第4节「分散还是集中」/ 《会见财经界》专访
I — 方法论骨架 (Interpretation)
集中投资的底层逻辑是一个简单推导:如果你真正看懂了一家公司(在能力圈内),你应该把钱投到最好的机会上;如果你同时持有很多只股票,说明你对每只都不够懂。
- 分散 = 对无知的保护:如果你需要买10只股票来分散风险,恰恰说明你对每只都不够了解。真正的理解带来的是确定性,而不是分散需求。
- 仓位反映理解度:一只股票的仓位比例应该由你的理解深度决定,而不是由"风险管理"公式决定。"一般的比例是0%-100%,取决于你自己懂多少"。
- 投的企业越多赚的越少:超出能力圈范围的持股,每增加一只都在稀释你对每只的注意力,增加犯错概率。
- 一辈子20个决策:如果一生只能投资20次(打孔卡片比喻),你会极其慎重地对待每一次出手。少决策、决策重。
- 集中是简单但非常难的事:难的不是集中本身,而是"真正看懂一家公司"这件事本身就极难。了解一只股票都很难,十只几乎是"mission impossible"。
- 钱少尤其要focus:资金量小的时候更没有资本分散,应该集中到最好的2-3个机会上。
- 分散叫理财不叫投资:撒胡椒面式的分散是理财(跟上大盘),不是投资(找到好公司重仓)。
A1 — 书中的应用 (Past Application)
案例 1: 段永平的极端集中持仓
- 问题: 段永平如何管理自己的投资组合?
- 方法论的使用: 他从始至终只真正投资过最多五六家公司,持有的公司一般在三家左右(苹果、茅台为核心)。买网易时把当时能动用的钱全部投进去。苹果仓位逐步加到60-70%。
- 结论: "好容易找到一个好价格的好股票,不集中是不明白的表现。"
- 结果: 网易约100倍回报,苹果和茅台均为长期重仓大牛股。芒格评价伯克希尔"除去10个投资就是个笑话"——57年历史,集中投资的收益几乎全部来自少数几个决策。
案例 2: 卡片打孔与决策频率
- 问题: 投资者应该以什么频率做出投资决策?
- 方法论的使用: 段永平引用巴菲特的打孔卡片比喻——一张只有20个孔的卡片,每次投资打一个孔,一生只有20次机会。他自己反省"大道这4年里只真正出手了一次,就是苹果,上一次出手是GE",平均约两年一家。在10年里大致看懂了不到10家企业,重手投了5家。
- 结论: "看准了出手就要狠。似懂非懂很难下手狠。"
- 结果: 极少的出手次数带来极高的单次决策质量和回报集中度。
A2 — 触发场景 (Future Trigger) ★
用户会在什么情境下需要这个 skill?
- 构建投资组合时犹豫持仓数量 — 用户有了一笔资金,正在纠结"买几只股票合适",是分散到8-10只还是集中到2-3只
- 已有持仓但仓位过轻想加仓时犹豫 — 用户看好某只股票但只敢放5%-10%仓位,想"平衡一下风险",在问仓位该怎么定
- 手中持股过多、精力分散导致每只都研究不深 — 用户持有10只以上股票,发现自己对每只都是"似懂非懂",频繁焦虑,想精简组合
语言信号 (用户的话里出现这些就应激活)
- "我买了10只股票分散风险" / "要不要多买几只平衡一下"
- "这只股票我只敢放5%仓位" / "不敢买太多比例"
- "投的企业越多赚的越少是怎么回事" / "为什么我持股越多反而越焦虑"
与相邻 skill 的区分
- 与
circle-of-competence(能力圈决策框架) 的区别: 能力圈解决"这只股票我懂不懂",本skill解决"懂了以后应该投多少钱"。能力圈是前提,集中投资是能力圈的仓位推论。 - 与
opportunity-cost(机会成本决策框架) 的区别: 机会成本解决"持有A还是换B"的比较问题,本skill解决"总共应该持几只"的数量问题。但两者在逻辑上互联——集中投资的理由之一是机会成本:每一块钱都应该投到最好的机会上。
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.
- 12d ago First seen · 137 lines · 194 tokens per session scan A 51ad0ac16057
concentrated-investing is a skill published in the GitHub repository kangarooking/duan-yongping-skill (48 stars, last pushed 4mo ago), licensed MIT. It adds 194 tokens to every session and 2,937 once invoked, about $0.0010 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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