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Agent Skill · 研究检索

think-like-warren-buffett(像沃伦·巴菲特一样思考)

think-like-warren-buffett 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

think-like-warren-buffett 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,674 个 Skill 里排第 21,733。

总安装 4,774周安装 195GitHub Stars 公开资料未说明下载 1,544核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:think-like-warren-buffett(像沃伦·巴菲特一样思考)
来源仓库:https://github.com/yixiao1032-publish/think-like-warren-buffett
安装命令:
openclaw skills install think-like-warren-buffett
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install think-like-warren-buffett

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

模拟巴菲特投资哲学,提供股票时间点分析与伯克希尔案例研究。适合价值投资者学习格雷厄姆式承销策略与长期决策方法。可生成买入/持有建议,结合财报与市场数据进行推演。安装命令:openclaw skills install think-like-warren-buffett。

输出仅为模拟观点,不构成真实投资建议,需自行核实风险。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install think-like-warren-buffett;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

think-like-warren-buffett 怎么安装?

在终端执行 openclaw skills install think-like-warren-buffett。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

think-like-warren-buffett 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

think-like-warren-buffett 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

think-like-warren-buffett 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

think-like-warren-buffett 用的人多吗?

公开数据是累计安装 4,774 次,近一周安装 195 次,下载 1,544 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

think-like-warren-buffett 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
think-like-warren-buffett

像沃伦·巴菲特一样思考 · 本页

4,774—需要联网MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
buffett-oracle
description
Point-in-time Buffett-style company analysis for stocks, Berkshire case studies, and BUY/PASS verdicts. Use when the user wants a Buffett/Graham underwriting memo, moat test, control-group comparison, or benchmark backtest grounded in cached company cards and strict decision-date discipline.
homepage
https://github.com/yixiao1032-publish/buffet-oracle
metadata
clawdbot
emoji
🔮
requires
env
[]
files

Buffett Oracle is a research skill for deciding whether a company deserves a BUY or PASS under a strict Buffett + Graham underwriting framework.

Use this skill when the user wants:

  • A Buffett-style memo on a public company, bank, utility, or crypto protocol
  • A point-in-time re-underwriting of a Berkshire decision
  • A moat explanation tied to hard numbers, not vibes
  • A clean BUY / PASS verdict instead of a hedged summary
  • A comparison against prior benchmark cases or same-era control groups

Read Order

Read only what you need:

  • buffett-oracle.md

Use for the Buffett Oracle persona, output structure, and portable prompt wording.

  • buffett_brain.md

Use for the Graham operating layer, 7 hard gates, named exemptions, and moat logic.

  • coverage_scope.md

Read before making any claim about benchmark completion or historical coverage.

  • company_cards/

Check first. If a matching card already exists, reuse it and do not re-fetch the filing.

  • backtest_results.md and analysis_index.json

Use for benchmark precedents and indexed case linkage.

  • universe_expansion.md and universe_expansion_index.json

Use for non-benchmark precedents without polluting the benchmark hit-rate.

  • methodology_audit.md

Read when the user asks how reliable the framework is, or whether the score implies predictive power.

  • gate_review.md

Read when the user asks why certain high-quality assets still fail the hard gates.

Non-Negotiables

  • Use only information that was public on or before the decision date.
  • Never describe the 29 benchmark rows as Buffett or Berkshire's full investment universe.
  • Never re-fetch a company that already has a cached card in company_cards/.
  • If any hard gate fails, default to PASS unless a named exemption clearly applies.
  • Every BUY needs two same-era control groups.
  • Lock the BUY / PASS conclusion before revealing what Buffett actually did.
  • Treat this as a research framework, not personalized investment advice.

Workflow

  1. Classify the request as INVESTMENT, SPECULATION, or TOO_HARD.

If it is SPECULATION or TOO_HARD, explain why and stop.

  1. Check company_cards/ for a cached <TICKER>_<YEAR>.json.

Reuse the card if present. Only fetch a new filing when no card exists.

  1. Run the 7 hard gates from buffett_brain.md.

Any failed gate means PASS, unless one of the named exemptions below is explicitly justified.

  1. Apply required overlays when triggered.

If g2 fails but moat still matters, add an owner-earnings note. If g6 fails but moat still matters, add a quality-multiple note. For new live or expansion memos, include management_veto as clear, watch, or fail.

  1. Write the moat paragraph.

If you cannot explain why competitors cannot replicate the business in 10 years, the answer is PASS.

  1. For every BUY, include the safety-margin math.

State owner's earnings or normalized earnings, value range, required return, and implied discount.

  1. Pick two same-era control-group companies that Buffett did not buy.

Run the same gate logic on them. If they also pass, explain the differentiator.

  1. Lock the verdict before reveal.

Only after the verdict should you reveal Buffett's action, later outcome, and whether the framework agreed.

  1. If you are updating this repository, save the card, append the memo to the correct markdown archive, and update the matching index JSON.

Named Exemptions

  • CRISIS_PREFERRED

For Goldman 2008 / BAC 2011 / GE 2008 style preferred-plus-warrant rescue structures.

  • INFRA_EXEMPTION

For rail and utility monopolies when monopoly status is clear and EV/EBITDA < 15x.

  • GROWTH_EXCEPTION

For high-ROIC compounders where weak raw FCF mostly reflects value-creating expansion rather than bad economics.

If you invoke an exemption, say so explicitly and defend it.

Output Contract

Use this summary block in the final answer:

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
CLASSIFICATION: [INVESTMENT / SPECULATION / TOO_HARD]
VERDICT: [BUY / PASS]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Hard Gates: [all passed / failed gates / exemption applied]
Named Exemption: [CRISIS_PREFERRED / INFRA_EXEMPTION / GROWTH_EXCEPTION / none]
Moat Type: [brand / network / switching cost / cost advantage / none]
Safety Margin: [owner's earnings, value range, required return, implied discount]
Key Conviction: [one sentence]
Key Risk: [one sentence]
Control Group: [Company A | Company B]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Then reveal:

  • what Buffett or Berkshire actually did
  • what happened afterward
  • whether the framework and Buffett agreed

Data Guidance

  • For US equities, prefer SEC EDGAR press-release or annual-report pages before full 10-K pulls.
  • For non-US companies, use official annual reports or equivalent filings.
  • For crypto or Web3, use on-chain and protocol-source documents, but keep the same anti-speculation bar.
  • Post-decision facts belong only in the reveal section, never in the underwriting logic.

Scope Reminder

The audited benchmark is a curated 29-case set. It is evidence of archive coverage, not a promise of forward hit rate and not the full Berkshire history.

平台分布

OpenClaw

87.44%
按下载量换算1,350

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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