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.
npx agentmods add skills/feicoder/skill-factory/sector-rotationnpx skills add FeiCoder/Skill-Factory --skill sector-rotationgit clone --depth 1 https://github.com/FeiCoder/Skill-FactoryWrote 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/feicoder/skill-factory/sector-rotation)<a href="https://agentmods.dev/skills/feicoder/skill-factory/sector-rotation"><img src="https://agentmods.dev/badge/skills/feicoder/skill-factory/sector-rotation.svg" alt="Measured on agentmods" 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 | $0.00041 | $0.00994 |
| Opus 5 | $0.00020 | $0.00497 |
| Sonnet 5 | $0.00008 | $0.00199 |
| Haiku 4.5 | $0.00004 | $0.00099 |
Grade A, and why
sector-rotation 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 5d 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.
What it actually says
行业轮动策略
基本概念
行业轮动是利用经济周期中不同行业的表现差异进行投资的策略。在一个完整的经济周期中，某些行业先启动，有些行业跟随。
核心理念
- 先导行业：基础设施、钢铁、水泥、机械
- 跟随行业：房地产、消费、文化
宏观经济与行业配置
自上而下分析框架
- 关注宏观经济运行指标
- 进行资产配置
- 调整风格和行业组合
行业收益来源
- 行业因子是股票收益的重要贡献因子
- 预测行业未来变动可获得超额收益
货币政策周期划分
M2作为货币周期指标
M2（广义货币）反映：
- 社会总需求变化
- 未来通货膨胀压力
- 货币政策效果
货币周期划分（2007-2011年案例）
| 周期 | 时间 | 特征 |
|---|---|---|
| 扩张期 | 约12个月 | 货币供应增加 |
| 紧缩期 | 约12个月 | 货币供应减少 |
平均周期长度：约12个月
行业分类
周期性行业
- 能源
- 材料
- 工业
- 金融
非周期性行业
- 可选消费
- 日常消费
- 信息
- 医药
- 电信
- 公用事业
轮动策略
1. M2行业轮动策略
策略逻辑：
- 货币扩张期 → 配置周期性行业
- 货币紧缩期 → 配置非周期性行业
操作：
- 滞后1个月操作（M2披露时滞）
- 等权重配置目标行业
实证结果
扩张期：周期性行业胜率67% 紧缩期：非周期性行业胜率100%
策略收益（2007.6-2011.12）：
- 顺周期轮动：-19.65%
- 行业平均：-40.50%
- 沪深300：-37.57%
- 超额收益：17.92%
2. 市场情绪轮动策略
策略逻辑：
- 利用趋势型技术指标
- 选择强势行业
- 设置止损控制风险
指标选择：
- MACD（常用参数：短期20周，长期40周）
- 评估行业绝对/相对趋势强度
实证效果（2003-2009）：
- 策略1收益率：1093.93%
- 策略2收益率：965.26%
- 沪深300收益率：129.45%
策略实施要点
M2轮动策略
- 数据获取：每月获取M2同比增速
- 移动平均：平滑M2波动（建议3个月移动平均）
- 周期判断：判断扩张/紧缩状态
- 行业配置：按周期配置相应行业
市场情绪策略
- 指标选择：趋势类技术指标（MACD、DMI等）
- 参数优化：通过历史回溯确定最优参数
- 止损设置：建议5%止损线
- 行业选择：选择相对强度最高的行业
A股行业轮动特点
- 货币驱动明显：M2是有效的行业轮动指标
- 周期性强：扩张/紧缩周期对行业影响显著
- 防御价值：非周期性行业在下跌市中防御性好
- 动量效应：行业动量在短期内有效
注意事项
- 考虑交易成本（建议扣除2%单次换仓成本）
- 滞后操作以避免假信号
- 定期重新评估M2与市场的关系
- 结合基本面进行行业选择
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.
- 5d ago First seen · 134 lines · 41 tokens per session scan A 157948289a85
sector-rotation is a skill published in the GitHub repository FeiCoder/Skill-Factory (10 stars, last pushed 6mo ago), licensed MIT. It adds 41 tokens to every session and 994 once invoked, about $0.0002 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 2026-08-31.
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