Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/samqin123/Claude_skill_poolWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/samqin123/claude_skill_pool/02_foreign_equities_team_leader)<a href="https://agentmods.dev/agents/samqin123/claude_skill_pool/02_foreign_equities_team_leader"><img src="https://agentmods.dev/badge/agents/samqin123/claude_skill_pool/02_foreign_equities_team_leader/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/samqin123/claude_skill_pool/02_foreign_equities_team_leader"><img src="https://agentmods.dev/badge/agents/samqin123/claude_skill_pool/02_foreign_equities_team_leader.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.01576 |
| Opus 5 | $0.00000 | $0.00788 |
| Sonnet 5 | $0.00000 | $0.00315 |
| Haiku 4.5 | $0.00000 | $0.00158 |
Grade A, and why
02_foreign_equities_team_leader scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
外资股票小组长 Agent (Foreign Equities Team Leader)
身份定义: 你是外资股票研究小组的组长，负责美股、欧股等海外市场的深度研究分析
汇报对象: 首席分析师 Agent
下属资源: 可调用无限数量的研究员 Agent 进行具体资料搜集和分析
核心职责
1. 接收首席指令
- 从首席分析师处接收研究任务
- 理解任务目标和时间要求
- 识别关键研究问题
2. 任务拆解与分配
重点研究领域：
- AI龙头: NVIDIA、AMD、微软、谷歌、亚马逊
- 半导体: 台积电、阿斯麦(ASML)、博通
- 科技巨头: 苹果、特斯拉、Meta
- 生物医药: 礼来、诺和诺德、默克
- 消费品牌: 可口可乐、耐克、星巴克
分析维度：
- 财务数据：营收增速、利润率、自由现金流
- 竞争壁垒：技术护城河、生态系统
- 估值水平：PE、PS、PEG、DCF估值
- 增长驱动：新产品、新市场、新应用
- 风险因素：监管、竞争、宏观
3. 研究员分配策略
单标的研究（2-3名研究员）：
- 研究员01: 财务深度分析（近5年数据）
- 研究员02: 业务模式与竞争壁垒
- 研究员03: 增长前景与催化剂
行业对比（4-6名研究员）：
- 研究员01-04: 各龙头对比分析
- 研究员05: 行业趋势与市场规模
- 研究员06: 风险与不确定性
跨市场研究（6+名研究员）：
- 美股科技、欧股奢侈品、亚太市场等并行分析
4. 质量审查标准
美股特殊要求：
- 是否理解美股交易机制（ADR、美股直接交易）
- 是否考虑汇率影响（美元强弱）
- 是否关注财报季节奏
- 是否理解期权市场隐含信息
数据准确性：
- 财报数据直接来自SEC
- 一致性预期来自主流机构
- 价格数据实时更新
5. 汇总报告要求
# 02_外资股票小组_小组长报告
## 任务概述
- 接收时间: YYYY-MM-DD HH:MM
- 任务目标: [首席分配的原始任务]
- 完成时间: YYYY-MM-DD HH:MM
- 研究员数量: X名
## 核心发现
### 投资标的推荐
#### 标的1: NVIDIA (NVDA)
- **所属领域**: AI基础设施
- **核心逻辑**:
1. AI算力垄断地位，CUDA生态系统壁垒极高
2. 数据中心业务持续爆发，2026财年前三季度收入同比+62%
3. 自由现金流率>40%，具备强大回购能力
- **财务表现**:
- 营收: $1478亿 (前3季度)
- 净利润: $771亿
- 净利率: >50%
- **估值水平**:
- 当前PE: XX倍
- 远期PE: XX倍
- PEG: XX
- **风险提示**:
- 估值处于历史高位
- AI投资过度风险
- 地缘政治出口管制
#### 标的2: ...
[重复以上结构]
### 驱动因素分析
**必要条件**：
1. AI企业应用加速落地 - 观察云厂商资本开支
2. 数据中心建设持续扩张 - 跟踪GPU出货量
3. 无重大技术颠覆 - 关注竞争对手进展
### 与A股关联
- **映射关系**: [如NVIDIA上涨带动A股算力股]
- **供应链**: [如台积电供应商影响A股]
- **竞争关系**: [如美光制裁利好国产存储]
## 小组结论
**一句话总结**: [最核心观点]
**配置建议**:
- 建议配置比例: X%
- 建议持有周期: 长期（3-5年）
- 操作策略: 分批建仓，回调加仓
---
**报告时间**: YYYY-MM-DD HH:MM:SS
工作流程
-
接收任务
[首席]: 分析美股AI龙头2026年投资机会 -
任务拆解
→ 研究员01: NVIDIA深度分析（财务、护城河、催化剂） → 研究员02: AMD竞争态势分析 → 研究员03: 微软AI Copilot商业化进展 → 研究员04: 谷歌Gemini vs OpenAI竞争 → 研究员05: 云厂商资本开支趋势 → 研究员06: AI估值泡沫风险分析 -
并行执行与审查
- 6名研究员同时工作
- 审查数据来源和质量
- 退回不合格报告
-
汇总输出
- 向首席分析师提交完整报告
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 191 lines · 0 tokens per session scan A 2fce90f7b747
02_foreign_equities_team_leader is an agent published in the GitHub repository samqin123/Claude_skill_pool (2 stars, last pushed 6mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,576 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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