Borrowing it
Nothing to install: this file belongs to belos-street/stock-analytics-skill. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/belos-street/stock-analytics-skill/main/.agents/skills/macro-sector-transmission/SKILL.mdgit clone --depth 1 https://github.com/belos-street/stock-analytics-skillWrote 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/skills/belos-street/stock-analytics-skill/macro-sector-transmission)<a href="https://agentmods.dev/skills/belos-street/stock-analytics-skill/macro-sector-transmission"><img src="https://agentmods.dev/badge/skills/belos-street/stock-analytics-skill/macro-sector-transmission/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/skills/belos-street/stock-analytics-skill/macro-sector-transmission"><img src="https://agentmods.dev/badge/skills/belos-street/stock-analytics-skill/macro-sector-transmission.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00063 | $0.03110 |
| Opus 5 | $0.00032 | $0.01555 |
| Sonnet 5 | $0.00013 | $0.00622 |
| Haiku 4.5 | $0.00006 | $0.00311 |
Grade A, and why
macro-sector-transmission 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 13d 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 — 462 lines — stays where its author put it; the contents beside it link to each section on GitHub.
宏观行业个股传导
技能核心定位
核心目标
用于宏观—行业—个股传导，聚焦宏观研究、资产配置、行业传导、自上而下研究。用户关注利率、汇率、财政、地产、出口、通胀、全球景气等变化时，真正想知道的不是宏观名词本身，而是这些变化会通过什么路径传导到哪些行业，再传导到哪些公司。
目标用户
- 宏观研究员：自上而下研究
- 策略分析师：行业配置决策
- 资产配置师：大类资产配置
- 行业研究员：关联行业研究
- 投资者：理解宏观影响
技能边界
可提供服务：
- 宏观变量传导路径
- 行业受益受损分析
- 投资时钟判断
- 行业配置建议
- 微观影响机制
不可提供服务：
- 精确预测
- 投资建议
- 内幕信息
传导框架总览
核心宏观变量
1. 利率周期
- 政策利率
- 无风险收益率
- 信用利差
2. 汇率周期
- 美元指数
- 人民币汇率
- 贸易加权汇率
3. 财政政策
- 财政支出
- 税收政策
- 地方政府债务
4. 地产周期
- 销售面积
- 新开工
- 投资增速
- 政策调控
5. 出口周期
- 贸易顺差
- 出口增速
- 份额变化
6. 通胀周期
- CPI/PPI
- 核心通胀
- 通胀预期
7. 信用周期
- 社融增速
- 信贷投放
- 信用利差
传导机制详解
一、利率传导
传导路径
利率变化
↓
融资成本变化
↓
企业投资意愿
↓
居民消费意愿
↓
经济增长 + 通胀
行业影响矩阵
| 行业 | 利率敏感度 | 传导方向 | 传导逻辑 |
|---|---|---|---|
| 银行 | 高 | 正面 | 息差扩大 |
| 券商 | 高 | 正面 | 交易活跃 |
| 保险 | 高 | 正面 | 固收配置 |
| 地产 | 极高 | 负面 | 融资成本↑ |
| 建筑 | 高 | 负面 | 融资成本↑ |
| 电力 | 中 | 负面 | 利率↑ |
| 航空 | 高 | 负面 | 美元债负担 |
| 负债率高企业 | 高 | 负面 | 利息支出↑ |
二、汇率传导
传导路径
汇率变化
↓
出口竞争力 + 进口成本
↓
贸易部门 + 制造业
↓
就业 + 收入
↓
消费 + 通胀
行业影响矩阵
| 行业 | 汇率敏感度 | 传导方向 | 传导逻辑 |
|---|---|---|---|
| 纺织服装 | 高 | 正面(贬) | 出口竞争力↑ |
| 电子 | 高 | 负面(升) | 进口元件成本↑ |
| 家电 | 中 | 正面(贬) | 出口竞争力↑ |
| 航空 | 高 | 负面(升) | 美元债负担↑ |
| 房地产 | 中 | 负面(升) | 资本外流↑ |
| 银行 | 中 | 复杂 | 双向影响 |
| 出口导向制造业 | 高 | 正面(贬) | 汇兑收益↑ |
| 进口依存度高 | 高 | 负面(贬) | 成本↑ |
三、财政传导
传导路径
财政扩张
↓
政府投资 + 购买
↓
基建 + 公共事业
↓
就业 + 收入
↓
消费 + 地产
行业影响矩阵
| 行业 | 财政敏感度 | 传导方向 | 传导逻辑 |
|---|---|---|---|
| 建筑 | 极高 | 正面 | 订单爆发 |
| 建材 | 高 | 正面 | 需求增加 |
| 工程机械 | 高 | 正面 | 开工率↑ |
| 交运 | 高 | 正面 | 物流需求↑ |
| 公用事业 | 中 | 正面 | 需求稳定 |
| 环保 | 高 | 正面 | 支出增加 |
| 军工 | 高 | 正面 | 采购增加 |
| 医疗 | 中 | 正面 | 财政投入↑ |
四、地产传导
传导路径
地产周期
↓
财富效应 + 托底经济
↓
消费 + 银行 + 家电
↓
地方政府 + 财政
行业影响矩阵
| 行业 | 地产敏感度 | 传导方向 | 传导逻辑 |
|---|---|---|---|
| 房地产 | 极高 | 正面 | 直接受益 |
| 银行 | 高 | 正面 | 资产质量 |
| 建筑建材 | 高 | 正面 | 需求增加 |
| 家电家居 | 高 | 正面 | 消费增加 |
| 白酒 | 中 | 正面 | 宴请消费 |
| 装修装饰 | 高 | 正面 | 增量需求 |
| 物业管理 | 中 | 正面 | 面积增加 |
| 园林景观 | 中 | 正面 | 新盘配套 |
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.
- 13d ago First seen · 462 lines · 63 tokens per session scan A ef145a62904c
macro-sector-transmission is a skill published in the GitHub repository belos-street/stock-analytics-skill (49 stars, last pushed 1mo ago), licensed MIT. It adds 63 tokens to every session and 3,110 once invoked, about $0.0003 per session on Opus 5. 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 2026-08-30.
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