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 skills add skloxo/TideTrading --skill sector-rotationgit clone --depth 1 https://github.com/skloxo/TideTradingWrote 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/skloxo/tidetrading/sector-rotation)<a href="https://agentmods.dev/skills/skloxo/tidetrading/sector-rotation"><img src="https://agentmods.dev/badge/skills/skloxo/tidetrading/sector-rotation/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/skloxo/tidetrading/sector-rotation"><img src="https://agentmods.dev/badge/skills/skloxo/tidetrading/sector-rotation.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 | $0.00039 | $0.02379 |
| Opus 5 | $0.00019 | $0.01189 |
| Sonnet 5 | $0.00008 | $0.00476 |
| Haiku 4.5 | $0.00004 | $0.00238 |
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 7d 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.
This is a copy
100% identical to sector-rotation — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.
行业轮动分析
概述
基于A股申万行业分类体系，通过景气度评分、动量排名、估值比较、资金流向四个维度进行行业轮动分析，输出行业超配/低配建议。
申万行业分类体系
一级行业（31个）
| 大类 | 行业 | 代码示例 |
|---|---|---|
| 上游周期 | 煤炭、有色、石油石化、钢铁、基础化工 | 煤炭ETF: 515220 |
| 中游制造 | 电力设备、机械设备、国防军工、汽车 | 新能源ETF: 516160 |
| 下游消费 | 食品饮料、家用电器、医药生物、美容护理 | 消费ETF: 510150 |
| TMT | 电子、计算机、通信、传媒 | 科技ETF: 515000 |
| 金融地产 | 银行、非银金融、房地产 | 金融ETF: 510230 |
| 公用事业 | 公用事业、交通运输、环保 | 红利ETF: 510880 |
行业周期属性
| 类型 | 行业 | 特征 | 驱动因子 |
|---|---|---|---|
| 强周期 | 煤炭/有色/钢铁/化工 | 盈利波动大，跟宏观紧密 | PPI、PMI、商品价格 |
| 弱周期 | 食品饮料/医药/公用 | 盈利稳定，防御属性 | CPI、消费数据 |
| 成长型 | 电子/计算机/电力设备 | 高PE高增速，政策敏感 | 产业政策、渗透率 |
| 金融 | 银行/非银/保险 | 利差驱动，与利率正相关 | 利率、社融、信贷 |
景气度评分框架
评分维度（满分100）
| 维度 | 权重 | 指标 | 评分规则 |
|---|---|---|---|
| 盈利增速 | 30% | 净利润同比增速 | >30%=30分, 15-30%=22分, 0-15%=15分, <0%=5分 |
| 盈利趋势 | 20% | 连续N季加速 | 加速3季+=20分, 2季=14分, 减速=-5分 |
| 景气指标 | 20% | PMI/开工率/价格 | 高位+上行=20分, 高位回落=12分, 低位=5分 |
| 政策支持 | 15% | 产业政策力度 | 明确利好=15分, 中性=8分, 利空=2分 |
| 估值安全 | 15% | PE历史分位 | <30%分位=15分, 30-50%=10分, >70%=3分 |
景气度变化信号
景气度上行信号（超配）:
1. 行业PMI连续2个月>50且环比改善
2. 龙头公司订单/收入同比加速
3. 产品价格上行（涨价周期）
4. 产能利用率>80%且在提升
5. 政策催化（补贴/准入/国产替代）
景气度下行信号（低配）:
1. 行业PMI连续2个月<50
2. 存货周转天数上升（库存积压）
3. 产品价格下行
4. 产能过剩（利用率<60%）
5. 政策收紧（环保/反垄断/集采）
行业动量排名方法
价格动量
def sector_momentum(sector_returns: pd.DataFrame, lookback: int = 60, skip: int = 5) -> pd.Series:
"""
Args:
sector_returns: 行业日收益率，columns=行业名
lookback: 回看窗口（交易日）
skip: 跳过最近N天（避免短期反转）
Returns:
行业动量得分排名
"""
cum_return = (1 + sector_returns).rolling(lookback).apply(lambda x: x[:-skip].prod() - 1)
return cum_return.iloc[-1].rank(ascending=False)
盈利动量
盈利动量 = 当季ROE同比变化 - 上季ROE同比变化
正值 = 盈利加速（超配信号）
负值 = 盈利减速（减配信号）
综合动量排名
综合得分 = 0.4 × 价格动量排名 + 0.3 × 盈利动量排名 + 0.3 × 资金流排名
取 Top 5 行业超配，Bottom 5 行业低配
产业链上下游传导
典型传导链条
上游（原材料）→ 中游（制造加工）→ 下游（消费/应用）
示例1: 锂电产业链
碳酸锂（上游）→ 正极材料（中游）→ 电池（中游）→ 新能源车（下游）
传导：锂价↑ → 正极成本↑ → 电池价格↑ → 车企毛利率↓
示例2: 半导体产业链
设备/材料（上游）→ 晶圆制造（中游）→ 封测（中游）→ 消费电子（下游）
传导：手机需求↑ → 封测订单↑ → 晶圆产能紧 → 设备资本开支↑
示例3: 地产产业链
土地/融资（上游）→ 开发建设（中游）→ 销售/物业（下游）
传导：政策宽松 → 销售回暖(下游先) → 新开工↑(中游) → 拿地↑(上游)
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.
- 7d ago First seen · 193 lines · 39 tokens per session scan A 8db0e9de5ed9
sector-rotation is a skill published in the GitHub repository skloxo/TideTrading (10 stars, last pushed 4d ago), licensed MIT. It adds 39 tokens to every session and 2,379 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to sector-rotation, differing in 0 lines, and is treated as a copy.
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