
Investment Team
AI Berkshire skill: 投研团队:四角色并行分析框架.
Install
npx skills add xbtlin/ai-berkshire --skill investment-team -g -a claude-code -y- Repository
- xbtlin/ai-berkshire17k
- Category
- Engineering
- Updated
- 3d ago
- License
- MIT
- Context cost
- Mediumabout 1,751 tokens
- Runs scripts
- No, instructions only
What it does
AI Berkshire skill: 投研团队:四角色并行分析框架. Source: skills/investment-team.md.
Codex adapter note
This skill is generated from skills/investment-team.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.
投研团队:四角色并行分析框架
对 $ARGUMENTS 进行团队化投资研究分析。使用 Team 工具创建真正的多Agent并行研究团队。
执行流程
第一步:展示团队框架
向用户展示以下团队结构,确认后启动:
| 角色 | 职责 | 分析框架 |
|---|---|---|
| team-lead(你自己) | 统筹协调、汇总研判、输出最终报告 | 四大师综合框架 |
| business-analyst | 商业模式 & 护城河分析 | 段永平视角 |
| financial-analyst | 财务报表 & 估值分析 | 巴菲特视角 |
| industry-researcher | 行业格局 & 竞争态势 | 芒格视角 |
| risk-assessor | 风险评估 & 管理层研判 | 李录视角 |
第一步半:AI研究偏见评估
在创建团队前,先向用户展示该公司的"AI可研究性"评估:
信息丰富度评级(决定研究策略):
| 等级 | 特征 | 研究策略调整 |
|---|---|---|
| A级(信息充裕) | 上市多年、券商覆盖广 | 团队重点放在反面检验和非共识视角,避免输出与市场一致的"正确的废话" |
| B级(信息适中) | 上市不久、覆盖有限 | 每个Agent的推算数据必须标注置信度,team-lead汇总时标注"数据充分度" |
| C级(信息稀缺) | 冷门/新上市/新兴市场 | 团队转为"第一性原理模式":不追求报告完整性,聚焦商业本质的几个核心问题 |
