Skills

Investment Checklist

AI Berkshire skill: 巴菲特价值投资买入前 Checklist.

Install

npx skills add xbtlin/ai-berkshire --skill investment-checklist -g -a claude-code -y
Repository
xbtlin/ai-berkshire17k
Category
Engineering
Updated
3d ago
License
MIT
Context cost
Lightabout 1,444 tokens
Runs scripts
No, instructions only

What it does

AI Berkshire skill: 巴菲特价值投资买入前 Checklist. Source: skills/investment-checklist.md.

Codex adapter note

This skill is generated from skills/investment-checklist.md so Claude Code and Codex users share one canonical workflow.

  • Treat $ARGUMENTS as the user's request in the current Codex thread.
  • When the source mentions Claude-only surfaces such as Task, Agent, WebSearch, Bash, Read, or Write, use the closest Codex capability available in this session: subagents when available, web search when needed, shell commands for local tools, and normal file edits for workspace files.
  • Use shared project tools from tools/ in this repository. Prefer running commands from the repository root with paths like python3 tools/financial_rigor.py ...; if the current thread starts outside the repo, locate the actual checkout path first instead of assuming a fixed home-directory path.
  • Before starting research, run the date command to confirm today's date; treat it as the baseline for "latest" data and state the data cutoff date in the report header. Never assume the current date from training data.
  • Preserve the research quality rules from AGENTS.md: cross-check financial data, use exact arithmetic tools for valuation/math, and clearly label uncertainty and source gaps.

巴菲特价值投资买入前 Checklist

对 $ARGUMENTS 执行巴菲特价值投资买入前 Checklist 分析。

支持输入格式:单个或多个公司,用逗号/顿号/空格分隔。例如:腾讯, 茅台, 英伟达 或 NVDA AAPL MSFT

执行流程

第一步:解析输入,识别所有待分析公司

从 $ARGUMENTS 中解析出所有公司名称/代码。对每家公司确定:

  • 公司全称、股票代码、上市交易所
  • 如果公司未上市,标记为"未上市"并给出简要说明(是否有间接投资途径),跳过完整Checklist

第一步半:AI研究偏见预警

对每家公司进行"信息丰富度"快速评级(A/B/C),并在报告中标注:

等级判断标准对Checklist的影响
A级上市多年、数据充裕正常执行,但警惕"共识陷阱", , 所有指标看起来都清晰不代表真的确定
B级数据有限需推算每个推算指标标注置信度,"好生意"判断加权考虑数据可靠性
C级信息极度稀缺不勉强填满六关表格,诚实标注"数据不足无法判断",聚焦可验证的核心问题

核心原则:Checklist的目标是排除坏选择。对于C级公司,"数据不足"不等于"不通过",也不等于"通过", , 应诚实标注为"灰色地带,需补充一手信息",而不是因为AI无法填满表格就判为否决。

段永平说过:"看不懂"有两种, , 一种是生意太复杂真的看不懂,一种是你还没花时间去看。AI研究的局限是容易把"资料少"和"看不懂"混为一谈。

第二步:并行数据收集

Read the whole SKILL.md on GitHub

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