ai-berkshire

Source#

• Repository: xbtlin/ai-berkshire
• Last source update: 2026-07-05
• Last verified: 2026-07-05

Tags#

Integration notes#

Repository is focused on tool/server interoperability; wrap in bounded worker contracts for production use.

worker.md example#

Starter worker.md contract mapped from this registry entry. Copy this file and adapt schemas, constraints, and statuses for your task.

---
id: ai-berkshire-repo-derived-worker
name: ai-berkshire Repo-Derived Worker
version: 1.0.0
source_registry_url: https://worker.md/registry/ai-berkshire/
source_repository: https://github.com/xbtlin/ai-berkshire
repository_default_branch: main
repository_language: Python
repository_license: MIT
repository_updated_at: 2026-07-05
worker_mode: agent-orchestration-worker
derivation_method: github_repository_metadata_plus_raw_readme
derivation_confidence: 0.95
derived_on: 2026-07-05
tags:
  - ai
  - ai-agent
  - anthropic
  - berkshire-hathaway
  - charlie-munger
  - china-stock
---

# ai-berkshire Repo-Derived Worker

## Repo-derived summary
- Registry summary: AI 时代的伯克希尔：基于 Claude Code / Codex 的价值投资研究框架。巴菲特·芒格·段永平·李录四大师方法论 + 多Agent并行研究。| AI-era Berkshire: a value investing research framework built for Claude Code / Codex. 4 masters' methodologies + multi...
- Repository description: AI 时代的伯克希尔：基于 Claude Code / Codex 的价值投资研究框架。巴菲特·芒格·段永平·李录四大师方法论 + 多Agent并行研究。| AI-era Berkshire: a value investing research framework built for Claude Code / Codex. 4 masters' methodologies + multi-agent adversarial analysis.
- Stars (snapshot): 9,821
- Primary language: Python
- Worker mode classification: agent-orchestration-worker

## Extracted from
- https://github.com/xbtlin/ai-berkshire
- https://github.com/xbtlin/ai-berkshire/blob/main/README.md
- https://api.star-history.com/svg?repos=xbtlin/ai-berkshire&type=Date

## Evidence notes (from repository text)
- README summary paragraph: > "Price is what you pay, value is what you get." — Warren Buffett > > 用 AI 重新定义投资研究的深度与效率。
- **AI Berkshire** 是一套同时兼容 Claude Code 与 Codex 的投资研究 Skill 合集，将巴菲特、芒格、段永平、李录四位价值投资大师的方法论系统化、结构化，通过 AI Agent 实现专业级投资研究。
- python3 tools/financial_rigor.py verify-market-cap \
- `/investment-team` 启动4个独立Agent**同时**研究一家公司。每个Agent各自搜索网络、交叉验证数据、独立给出结论。这不是把一个prompt拆成四段——是4个"分析师"各自做了完整的研究，Team Lead再综合。
- 一个人直接问AI，上下文窗口是一个。4个Agent并行，等于4倍的搜索量、4倍的信息源、4个独立视角。
- │ Agent 1 │ Agent 2 │ Agent 3 │ Agent 4 │

## Installation hints found in README
- `npm install -g @anthropic-ai/claude-code`
- `npm install -g @openai/codex`

## worker.md contract (derived starter)
Purpose: Execute one orchestrated agent task as a bounded worker step.

### Input schema
```json
{
  "type": "object",
  "additionalProperties": false,
  "required": [
    "run_id",
    "task",
    "context"
  ],
  "properties": {
    "run_id": {
      "type": "string"
    },
    "task": {
      "type": "string"
    },
    "context": {
      "type": "object"
    }
  }
}
```

### Output schema
```json
{
  "type": "object",
  "additionalProperties": false,
  "required": [
    "run_id",
    "status",
    "result"
  ],
  "properties": {
    "run_id": {
      "type": "string"
    },
    "status": {
      "type": "string",
      "enum": [
        "ok",
        "retryable_error",
        "invalid_request",
        "invalid_output"
      ]
    },
    "result": {
      "type": "object"
    }
  }
}
```

### Constraints
- timeout_seconds: 30
- max_attempts: 2
- idempotency_key: run_id
- status_enum: [ok, retryable_error, invalid_request, invalid_output]
- notes: adapt to concrete APIs/classes documented in this repository before production use

## How this should be used
1. Treat this file as a repo-derived starter profile, not a claim of an official repository API contract.
2. Replace schemas with exact interfaces from code/docs you adopt.
3. Keep execution bounded and auditable using worker protocol constraints.

How to use#

• Save this as a worker spec file (for example: ai-berkshire-my-task.worker.md).
• Replace the input/output schemas and purpose with your real bounded task.
• Enforce schema validation + timeout + retry policy in your runtime before production use.

Citation#

Reference URL: https://worker.md/registry/ai-berkshire/

Source URL: https://github.com/xbtlin/ai-berkshire