基于宏观-行业-个股三层分析框架，数据驱动的专业投资分析。
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Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
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Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
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Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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基于宏观-行业-个股三层分析框架，数据驱动的专业投资分析。
/analyze 588000 # 分析ETF
/analyze 002594 # 分析A股
/analyze 00700 # 分析港股
/analyze 比亚迪 # 用名称也可以
┌─────────────────────────────────────────────────┐
│ 投资分析框架 │
├─────────────────────────────────────────────────┤
│ 1. 宏观环境（大势）20分 │
│ ├─ 市场周期：牛市/熊市/震荡 │
│ ├─ 指数趋势：沪深300 vs MA20 │
│ ├─ 资金环境：北向资金流向 │
│ └─ 市场情绪：涨跌比例 │
├─────────────────────────────────────────────────┤
│ 2. 行业分析（中观）20分 │
│ ├─ 板块强弱：相关板块排名 │
│ ├─ 资金流向：板块净流入 │
│ ├─ 相对强度：ETF横向对比 │
│ └─ 政策催化：行业政策动向 │
├─────────────────────────────────────────────────┤
│ 3. 个股分析（微观）60分 │
│ ├─ 趋势：均线排列+多周期共振 │
│ ├─ 动能：MACD+RSI │
│ ├─ 量价：量比+量价配合+背离 │
│ └─ 位置：ATR止损+支撑压力 │
├─────────────────────────────────────────────────┤
│ 4. 交易策略 │
│ ├─ 买点：理想/激进价位 │
│ ├─ 止损：ATR动态止损 │
│ └─ 目标：压力位参考 │
└─────────────────────────────────────────────────┘
| 优先级 | 来源 | 用途 |
|---|---|---|
| 1 | fetch_full_analysis.py |
宏观+行业+技术全套数据 |
| 2 | 用户配置文件 | 持仓、关注方向、投资风格 |
| 3 | WebSearch | 仅用于财报、公告、研报 |
cd "股市信息" && python3 scripts/fetch_full_analysis.py <代码>
港股：
cd "股市信息" && python3 scripts/fetch_full_analysis.py 00700 --market hk
脚本输出的核心模块：
| 模块 | 字段 | 说明 |
|---|---|---|
| 宏观 | macro.indices |
主要指数涨跌 |
macro.market_trend |
牛市/熊市/震荡判断 | |
macro.north_flow |
北向资金流向 | |
macro.market_sentiment |
涨跌家数比 | |
| 行业 | sector.related_sectors |
相关板块表现 |
sector.sector_flow |
板块资金流入 | |
sector.etf_comparison |
ETF横向对比 | |
sector.relative_strength |
领涨/跟涨/跟跌 | |
| 技术 | technical.trend |
均线趋势 |
technical.macd |
MACD状态 | |
technical.rsi |
RSI超买超卖 | |
technical.atr |
ATR止损参考 | |
technical.volume |
量价配合 | |
| 评分 | score |
100分制综合评分 |
股市信息/Config/Holdings.md → 是否已持有
股市信息/Config/Watchlist.md → 关注方向
股市信息/Config/Profile.md → 投资风格
只在以下情况使用：
必须标注来源和日期
脚本输出 macro 字段：
{
"market_trend": {
"cycle": "牛市",
"cycle_score": 2,
"hs300_vs_ma20": 1.51
},
"north_flow": {
"5d_total": 150.5,
"consecutive_days": 3,
"direction": "流入",
"signal": "外资积极"
},
"market_sentiment": {
"up_ratio": 65.2,
"sentiment": "偏乐观"
}
}
市场周期判断规则：
| 条件 | 周期 | 得分 |
|---|---|---|
| 沪深300 > MA20 且 60日涨幅>0 | 牛市 | +12 |
| 沪深300 < MA20 且 60日跌幅>10% | 熊市 | +4 |
| 其他 | 震荡 | +8 |
北向资金信号：
| 5日累计 | 方向 | 得分 |
|---|---|---|
| > 50亿 | 持续流入 | +8 |
| < -50亿 | 持续流出 | +2 |
| 其他 | 中性 | +4 |
脚本输出 sector 字段：
{
"related_sectors": [
{"name": "半导体概念", "change": 2.34, "turnover": 5.95},
{"name": "存储芯片", "change": 1.13, "turnover": 4.27}
],
"sector_flow": [
{"name": "半导体概念", "net_flow": 38.8亿, "net_ratio": 0.88}
],
"etf_comparison": [
{"code": "159995", "name": "芯片ETF", "change": 1.16},
{"code": "588000", "name": "科创50ETF", "change": -0.38}
],
"relative_strength": "跟跌"
}
相对强度判断：
| ETF vs 同类 | 相对强度 | 得分 |
|---|---|---|
| 涨幅排名前30% | 领涨 | +15 |
| 涨幅接近平均 | 跟涨 | +10 |
| 涨幅排名后30% | 跟跌 | +5 |
板块资金流向：
| 相关板块净流入 | 信号 | 得分 |
|---|---|---|
| 多数流入 | 板块热度高 | +5 |
| 多数流出 | 板块退潮 | +0 |
{
"trend": {
"status": "多头排列",
"score": 2
}
}
| 均线状态 | 得分 |
|---|---|
| 多头排列（MA5>MA10>MA20>MA60） | +25 |
| 偏多（价格>MA20） | +15 |
| 纠缠 | +10 |
| 空头排列 | +5 |
{
"macd": {"signal": "多头"},
"rsi": {"value": 65, "signal": "中性"}
}
| MACD状态 | 得分 |
|---|---|
| 金叉/多头 | +10 |
| 死叉/空头 | +5 |
| RSI状态 | 得分 |
|---|---|
| 中性(30-70) | +5 |
| 超买(>70)或超卖(<30) | +3 |
{
"volume": {
"ratio": 0.87,
"vol_price": "量价平稳"
}
}
| 量价关系 | 得分 |
|---|---|
| 放量上涨 | +10 |
| 量价平稳 | +6 |
| 缩量上涨 | +4 |
| 放量下跌 | +2 |
{
"atr": {
"value": 0.0382,
"stop_loss": 1.4966,
"stop_loss_pct": -4.86
}
}
止损建议：
stop_loss| 维度 | 满分 | 评估内容 |
|---|---|---|
| 宏观 | 20 | 市场周期+北向资金 |
| 行业 | 20 | 相对强度+板块资金 |
| 技术 | 60 | 趋势+动能+量价+位置 |
| 总分 | 100 |
评分等级：
| 分数 | 等级 | 建议 |
|---|---|---|
| 80-100 | 强势 | 可积极参与 |
| 65-79 | 偏强 | 可适度参与 |
| 50-64 | 中性 | 观望为主 |
| 35-49 | 偏弱 | 谨慎 |
| 0-34 | 弱势 | 回避 |
# [代码] [名称] 深度分析
**分析时间**：YYYY-MM-DD HH:MM
**数据来源**：AKShare v3.0
**分析框架**：宏观-行业-个股
---
## 快速摘要
| 层级 | 判断 | 得分 |
|------|------|------|
| 宏观环境 | 牛市/熊市/震荡 | XX/20 |
| 行业强度 | 领涨/跟涨/跟跌 | XX/20 |
| 技术形态 | 多头/空头/震荡 | XX/60 |
| **综合** | **强势/偏强/中性/偏弱/弱势** | **XX/100** |
---
## 一、宏观环境（大势）
### 市场周期
- 沪深300：XXXX (+XMake data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
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Solid pick for teams standardizing on skills: analyze is focused, and the summary matches what you get after install.
Useful defaults in analyze — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
analyze fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
analyze is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
analyze reduced setup friction for our internal harness; good balance of opinion and flexibility.
analyze has been reliable in day-to-day use. Documentation quality is above average for community skills.
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I recommend analyze for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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