
Thesis Drift
AI Berkshire skill: 投资论文漂移检测:分清事实变化与措辞变化.
Install
npx skills add xbtlin/ai-berkshire --skill thesis-drift -g -a claude-code -y- Repository
- xbtlin/ai-berkshire17k
- Category
- Engineering
- Updated
- 3d ago
- License
- MIT
- Context cost
- Lightabout 1,470 tokens
- Runs scripts
- No, instructions only
What it does
AI Berkshire skill: 投资论文漂移检测:分清事实变化与措辞变化. Source: skills/thesis-drift.md.
Codex adapter note
This skill is generated from skills/thesis-drift.md so Claude Code and Codex users share one canonical workflow.
- Treat
$ARGUMENTSas 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 likepython3 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
datecommand 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.
投资论文漂移检测:分清事实变化与措辞变化
对 $ARGUMENTS 执行投资论文漂移检测。
支持输入格式:
公司名 旧报告路径 新报告路径, 指定两份研究报告或论文快照进行对比公司名 reports/{公司名}-thesis-旧日期.md reports/{公司名}-thesis-新日期.md, 对比两份带日期的论文快照公司名, 自动查找reports/{公司名}-thesis.md及同目录历史快照;如果没有基线则转入缺失基线处理
"当事实改变时,我就改变想法。你呢?", , 凯恩斯
"股价波动不是论文漂移,事实变了才是。", , AI Berkshire
设计理念
长期持仓最难的不是每天读新闻,而是区分三件事:
- 事实改变:收入、利润率、竞争格局、管理层行为、资本配置发生可验证变化
- 价格改变:市场情绪或估值倍数变化,但生意本身未变
- 措辞改变:两份报告表达不同,但底层证据和判断没有变化
投资论文漂移检测的目标是:只在证据变化时承认论文变化。不能因为报告换了写法就制造漂移,也不能因为股价涨跌就误判基本面。
本 Skill 依赖 /thesis-tracker 输出的结构化维度:核心假设清单、红线清单、估值锚点、追踪记录表。没有这些结构时,先补齐基线,再做漂移检测。
