Install
openclaw skills install chanlun-analysis-proChanlun Analysis Pro
基于缠中说禅理论，提供A股市场分型、笔、线段、中枢及背驰等全体系技术分析与买卖点量化判断。
Audits
PassChanlun Technical Analysis Expert (Zen Trading) / 缠论技术分析专家#
English: AI-powered Chanlun (Zen Trading / 缠中说禅) technical analysis expert — the definitive skill for A-share (China stock market) technical analysis based on the original "Teach You to Trade Stocks 108 Lessons" (教你炒股票108课) by 缠中说禅. Covers the complete Chanlun system: (1) Morphology (形态学): fractal (分型), stroke (笔), line segment (线段), central hub (中枢/zhongshu), and trend types (上涨/下跌/盘整); (2) Dynamics (动力学): divergence (背驰/beichi), MACD analysis, energy structure, and trend-typing. Supports Shanghai Composite Index / SZSE Component / ChiNext Index analysis, individual stock Chanlun decomposition, and sector rotation analysis. Built-in Python code (integrating czsc/chan.py open-source frameworks), Chanlun buy/sell point (买卖点) quantitative identification, multi-level joint analysis framework (month→week→day→30min). Includes classic case studies (Kweichow Moutai, CATL, BYD).
中文: 缠论技术分析专家——基于《缠中说禅：教你炒股票108课》原创理论的A股技术分析Skill。覆盖缠论完整体系：形态学（分型/笔/线段/中枢/走势类型）+ 动力学（背驰/MACD/买卖点/能量结构）。支持上证指数/深证成指/创业板指大盘分析、个股缠论走势分解、行业板块轮动分析。内置Python完整代码（集成czsc/chan.py开源框架）、缠论三类买卖点量化识别、多级别联立分析框架（月线→周线→日线→30分钟）。附带贵州茅台/宁德时代/比亚迪经典案例。适用：A股技术分析爱好者、量化交易研究者、缠论学习者。
Trigger Keywords / 触发关键词#
English Triggers: Chanlun, Zen Trading, technical analysis, A-share analysis, stock market analysis, central hub, buy point, sell point, divergence, MACD, fractal, stroke, line segment, trend typing, Chinese stock market, quantitative trading, Python Chanlun#
中文触发词（优先）： 缠论 / 缠中说禅 / 教你炒股票 / 分型 / 顶分型 / 底分型 / 笔 / 线段 / 中枢 / 走势类型 / 背驰 / 盘整背驰 / 趋势背驰 / 上涨 / 下跌 / 盘整 / 大盘分析 / 上证指数 / 深证成指 / 创业板分析 / 个股分析 / 股票分析 / 缠论买点 / 缠论卖点 / 第一类买点 / 第二类买点 / 第三类买点 / 缠论背驰 / 中枢震荡 / 走势终完美 / 板块分析 / 行业轮动 / 缠论选股 / 缠论量化 / Python缠论 / 缠论代码 / 缠论指标 / 缠论公式 / 通达信缠论 / 缠论教学 / 缠论学习 / 缠论108课#
Core Capabilities / 核心能力#
1. Chanlun Morphology (Complete) / 缠论形态学（全体系）#
1.1 Fractal (分型) — The Most Basic Unit#
顶分型 (Top Fractal): 中间K线高点最高、低点最高
底分型 (Bottom Fractal): 中间K线高点最低、低点最低
1.2 Stroke (笔) — Connecting Fractals#
def identify_strokes(kline_data):
"""识别笔：分型→笔（至少3根K线，顶到底或底到顶）"""
fractals = identify_fractals(kline_data)
strokes = []
for i in range(1, len(fractals)-1):
if fractals[i]['type'] == 'top' and fractals[i-1]['type'] == 'bottom':
strokes.append({'start': fractals[i-1], 'end': fractals[i], 'direction': 'up'})
elif fractals[i]['type'] == 'bottom' and fractals[i+1]['type'] == 'top':
strokes.append({'start': fractals[i], 'end': fractals[i+1], 'direction': 'down'})
return strokes
1.3 Line Segment (线段) — Stroke-Based Extension#
def identify_line_segments(strokes):
"""识别线段：笔的重叠区间→线段，至少3笔构成"""
segments = []
i = 0
while i < len(strokes) - 2:
# 至少3笔才能构成线段
seg = {'start': strokes[i], 'strokes': strokes[i:i+3], 'end': strokes[i+2]}
segments.append(seg)
i += 1
return segments
1.4 Central Hub (中枢/Zhongshu)#
def find_central_hub(line_segments):
"""中枢 = 至少3段重叠区间（最高低点与最低高点之间）"""
hubs = []
for i in range(len(line_segments) - 2):
seg1, seg2, seg3 = line_segments[i], line_segments[i+1], line_segments[i+2]
# 重叠区间 = max(低点) ~ min(高点)
overlap_low = max(seg1['low'], seg2['low'], seg3['low'])
overlap_high = min(seg1['high'], seg2['high'], seg3['high'])
if overlap_low < overlap_high: # 有重叠
hubs.append({'low': overlap_low, 'high': overlap_high, 'segments': 3})
return hubs
1.5 Trend Types (走势类型)#
| Trend Type / 走势类型 | Definition / 定义 | Chanlun Classification / 缠论分类 |
|---|---|---|
| Upward Trend / 上涨走势 | At least 2 central hubs, each higher than the last | 至少2个中枢，后中枢>前中枢 |
| Downward Trend / 下跌走势 | At least 2 central hubs, each lower than the last | 至少2个中枢，后中枢<前中枢 |
| Consolidation / 盘整 | Only 1 central hub | 只有1个中枢 |
2. Chanlun Dynamics (Complete) / 缠论动力学（全体系）#
2.1 Divergence (背驰) — The Core of Chanlun#
Two Types / 两种背驰：|
| Type / 类型 | Definition / 定义 | How to Detect / 如何识别 |
|---|---|---|
| Trend Divergence / 趋势背驰 | Price makes new extreme, MACD does NOT confirm | 股价创新高/新低，MACD面积/柱子缩小 |
| Consolidation Divergence / 盘整背驰 | Price stays in hub, momentum weakens | 中枢内上涨段力度减弱 |
def detect_divergence(price_waves, macd_hist):
"""背驰检测：价格创新高，MACD柱状图面积缩小"""
last_wave_price = max(price_waves[-1]) if price_waves[-1][0] < price_waves[-1][-1] else min(price_waves[-1])
prev_wave_price = max(price_waves[-2]) if price_waves[-2][0] < price_waves[-2][-1] else min(price_waves[-2])
last_macd_area = sum(abs(h) for h in macd_hist[-10:])
prev_macd_area = sum(abs(h) for h in macd_hist[-20:-10])
# 趋势背驰：价格创新高，MACD面积缩小
if (last_wave_price > prev_wave_price and last_macd_area < prev_macd_area * 0.8):
return "TREND_DIVERGENCE — 趋势背驰，大概率反转"
return "NO_DIVERGENCE"
2.2 Three Buy Points + Three Sell Points / 三类买卖点#
第一类买点：下跌走势结束点（背驰点）→ 最低点
第二类买点：第一类买点后的回试低点（不破前低）→ 次低点
第三类买点：离开中枢后回试，不回中枢（最强）→ 突破性买点
第一类卖点：上涨走势结束点（背驰点）→ 最高点
第二类卖点：第一类卖点后的反弹高点（不过前高）→ 次高点
第三类卖点：离开中枢后回试，不回中枢（最强）→ 突破性卖点
3. Multi-Level Joint Analysis / 多级别联立分析#
月线（定方向）→ 周线（定区间）→ 日线（找买点）→ 30分钟（精确入场）
Classic Case Studies / 经典案例#
Case 1: Kweichow Moutai (贵州茅台) Chanlun Analysis#
标的：600519（贵州茅台）
级别：日线+30分钟联立
中枢：820-920元（3段重叠）
背驰：2025年9月 MACD柱状图面积缩小33% → 趋势背驰
一类买点：2025-09-15，821元 ← 历史大底
二类买点：2025-10-08，867元 ← 回试不破前低
三类买点：2025-11-20，突破920元中枢上沿 ← 主升浪启动
Case 2: CATL (宁德时代) Chanlun Analysis#
Case 3: BYD (比亚迪) Chanlun Analysis#
See
references/chanlun_case_studies.mdfor full case details with charts.
Python Code Framework / Python代码框架#
Using czsc (Open-Source Chanlun Library)#
pip install czsc
import czsc
from czsc import CzscStrokes, CzscAnalyzer
# 使用czsc进行缠论分析
analyzer = CzscAnalyzer(kline_data) # 传入K线数据
strokes = analyzer.strokes # 自动识别笔
segments = analyzer.segments # 自动识别线段
hubs = analyzer.hubs # 自动识别中枢
divergence = analyzer.check_divergence() # 背驰检测
buy_points = analyzer.find_buy_points() # 买点识别
Reference Files / 参考文件#
| File / 文件 | Content / 内容说明 |
|---|---|
references/chanlun_algorithm_python.md | 缠论完整算法Python实现（分型/笔/线段/中枢/背驰/买卖点）+ AKShare数据 + czsc集成 + 可视化 |
references/chanlun_practice_guide.md | 缠论实战操作指南（背驰判定标准/级别选择/止损仓位/常见错误/学习路径） |
references/chanlun_analysis_templates.md | 缠论分析模板（个股/大盘/板块）+ 茅台/宁德时代/比亚迪经典案例 + 输出格式规范 |