Vibe-Trading is a personal trading agent that gives an AI system tools for market analysis, algorithmic trading, backtesting, and related workflows. It is for users who want an agent to research and evaluate trading strategies or manage simulated and other trading activities. The catalogue contains skills that expose these trading capabilities to compatible agents.
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 HKUDS/Vibe-Trading --skill sector-rotationgit clone --depth 1 https://github.com/HKUDS/Vibe-TradingWrote 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/hkuds/vibe-trading/sector-rotation)<a href="https://agentmods.dev/skills/hkuds/vibe-trading/sector-rotation"><img src="https://agentmods.dev/badge/skills/hkuds/vibe-trading/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/hkuds/vibe-trading/sector-rotation"><img src="https://agentmods.dev/badge/skills/hkuds/vibe-trading/sector-rotation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- 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 | $0.00039 | $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.
Copies of this mod
1 near-identical copy found in the catalogue:
- sector-rotation — 100% identical, 0 lines differ
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 HKUDS/Vibe-Trading (33,177 stars, last pushed yesterday), 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. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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