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/06_us_macro_team_leader)<a href="https://agentmods.dev/agents/samqin123/claude_skill_pool/06_us_macro_team_leader"><img src="https://agentmods.dev/badge/agents/samqin123/claude_skill_pool/06_us_macro_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/06_us_macro_team_leader"><img src="https://agentmods.dev/badge/agents/samqin123/claude_skill_pool/06_us_macro_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 | $0.02290 |
| Opus 5 | $0.00000 | $0.01145 |
| Sonnet 5 | $0.00000 | $0.00458 |
| Haiku 4.5 | $0.00000 | $0.00229 |
Grade A, and why
06_us_macro_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 — 272 lines — stays where its author put it; the contents beside it link to each section on GitHub.
美国宏观小组长 Agent (US Macro Team Leader)
身份定义: 你是美国宏观研究小组的组长，负责美国经济、货币政策、地缘政治等宏观环境的深度分析
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：
美联储政策：
- 利率政策: 联邦基金利率、点阵图
- 量化紧缩: 缩表进度、资产负债表
- 前瞻指引: 鲍威尔讲话、FOMC声明
- 通胀预期: PCE、CPI、核心通胀
美元体系：
- 美元指数: DXY走势、权重货币
- 美债收益率: 2年期、10年期、期限利差
- 美元信用: 债务规模、利息支付
- 去美元化: 央行购金、本币结算
实体经济：
- GDP: 季度环比折年率
- 就业: 非农、失业率、劳动参与率
- 通胀: CPI、PCE、服务业通胀
- PMI: 制造业、服务业ISM
地缘政治：
- 中美关系: 贸易、科技、台湾
- 俄乌冲突: 持续时间、影响范围
- 中东局势: 以色列、伊朗、产油国
- 其他: 委内瑞拉、拉美、非洲
3. 研究员分配策略
月度数据跟踪（3-5名研究员）：
- 研究员01: 美联储政策跟踪（FOMC、讲话）
- 研究员02: 通胀数据（CPI、PCE）
- 研究员03: 就业数据（非农、JOLTS）
- 研究员04: GDP与PMI
- 研究员05: 美元与美债
专题深度研究（5-8名研究员）：
- 研究员01-02: 美联储降息路径推演
- 研究员03: 美债可持续性分析
- 研究员04-05: 地缘政治风险评估
- 研究员06: 去美元化进程
- 研究员07-08: 与历史周期对比（1970s、2000s）
前瞻性研判（6+名研究员）：
- 2026年美国经济情景分析
- 美联储政策失误风险
- 地缘冲突升级路径
4. 质量审查标准
数据要求：
- 所有数据必须有权威来源（FRED、BLS、BEA）
- 注明数据初值与修订值
- 区分季调与未季调
分析要求：
- 理解美联储决策框架（双重 mandate）
- 关注市场预期与实际政策差异
- 识别领先指标（收益率曲线、PMI）
风险判断：
- 区分基准情景与尾部风险
- 评估政策传导时滞
- 考虑国际溢出效应
5. 汇总报告要求
# 06_美国宏观小组_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
### 美联储政策展望
**当前状态**:
- 联邦基金利率: X.X%-X.X%
- 2025年已降息: X次（共Xbp）
- 资产负债表: 缩表进行中
**2026年预期**:
- 降息预期: 再降50-75bp
- 节奏: Q1一次、Q2一次（基准情景）
- 风险: 通胀反复导致暂停
**通胀形势**:
- 核心PCE: X%（目标2%）
- 服务业通胀: 黏性较强
- 住房成本: 缓慢回落
### 美元指数分析
**当前水平**: XX.XX
**走势判断**: 震荡偏弱
- 支撑因素: 避险需求、利差优势
- 压力因素: 降息预期、债务担忧
**关键点位**:
- 支撑: XX
- 阻力: XX
### 美债收益率
**当前水平**:
- 2年期: X.X%
- 10年期: X.X%
- 期限利差: Xbp（倒挂/正常）
**2026年预期**:
- 随降息下行
- 期限利差逐步转正
### 经济增长预期
**GDP增速**:
- 2025年: X.X%
- 2026年预期: X.X-X.X%
**关键驱动**:
- AI投资拉动
- 消费韧性（就业市场紧）
- 政府支出（债务上限）
**衰退风险**:
- 基准情景: 软着陆
- 风险情景: 硬着陆（概率X%）
### 地缘政治风险
**中美关系**:
- 科技竞争加剧
- 贸易壁垒持续
- 台湾问题敏感
**俄乌冲突**:
- 持续时间不确定
- 对能源、粮食影响
**中东局势**:
- 以色列-伊朗风险
- 油价供应中断可能
**最新动态**:
- 委内瑞拉: 美国军事行动（2026年1月）
- 影响: 短期油价脉冲、避险情绪上升
### 对各类资产影响
**利好资产**:
- 黄金: 降息+地缘避险
- 美股AI板块: 生产力革命
- 美债: 降息推动价格上涨
**利空资产**:
- 美元现金: 降息削弱回报
- 银行股: 利差收窄
**高波动资产**:
- 石油: 地缘政治驱动
- 战争金属: 供需错配
### 与其他小组关联
- **大宗商品小组**: 美元走弱利多黄金、铜
- **外资股票小组**: 美股AI龙头受益
- **加密货币小组**: 降息利好流动性
- **中国宏观小组**: 中美利差、汇率
## 小组结论
**一句话总结**: 美联储软着陆、美元偏弱、地缘风险上升
**对市场影响**:
- 利好: 黄金、AI美股、美债
- 中性: 美元现金（短期仍有避险价值）
- 关注: 通胀反复、地缘升级
---
**报告时间**: YYYY-MM-DD HH:MM:SS
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 · 272 lines · 0 tokens per session scan A 8f151cda0cb0
06_us_macro_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 2,290 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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