longbridge-technical

Core technical-indicator signal engine for stocks listed in HK / US / A-share / Singapore via Longbridge Securities. Computes and interprets MACD, KDJ, RSI, Bollinger Bands, EMA, ADX, and OBV from OHLCV data; combines multi-dimensional votes (trend / mean-reversion / volume-price) to produce a composite buy / sell / neutral signal. Triggers: "技术指标", "MACD", "KDJ", "RSI", "布林带", "布林线", "EMA", "ADX", "OBV", "金叉", "死叉", "超买", "超卖", "技术分析", "趋势指标", "量价", "技術指標", "布林帶", "技術分析", "超買", "超賣", "technical indicator", "MACD signal", "KDJ overbought", "RSI oversold", "Bollinger Bands", "moving average", "golden cross", "death cross", "technical analysis".

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npx skills add https://github.com/majiayu000/claude-skill-registry --skill longbridge-technical

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name	longbridge-technical
description	Core technical-indicator signal engine for stocks listed in HK / US / A-share / Singapore via Longbridge Securities. Computes and interprets MACD, KDJ, RSI, Bollinger Bands, EMA, ADX, and OBV from OHLCV data; combines multi-dimensional votes (trend / mean-reversion / volume-price) to produce a composite buy / sell / neutral signal. Triggers: "技术指标", "MACD", "KDJ", "RSI", "布林带", "布林线", "EMA", "ADX", "OBV", "金叉", "死叉", "超买", "超卖", "技术分析", "趋势指标", "量价", "技術指標", "布林帶", "技術分析", "超買", "超賣", "technical indicator", "MACD signal", "KDJ overbought", "RSI oversold", "Bollinger Bands", "moving average", "golden cross", "death cross", "technical analysis".
license	MIT
metadata	{"author":"longbridge","version":"1.0.0","risk_level":"read_only","requires_login":false,"default_install":true,"requires_mcp":false,"tier":"read"}

longbridge-technical

Computes seven classic technical indicators from 200 days of OHLCV data and produces a composite buy / sell / neutral signal via a multi-dimensional voting mechanism.

Response language: match the user's input language — Simplified Chinese / Traditional Chinese / English.

When to use

"NVDA MACD 金叉了吗", "TSLA RSI 超买了吗", "700.HK 技术指标怎么看"
"600519.SH 布林带收口", "AAPL 技術分析信號", "ADX 趋势强吗"
"technical analysis for NVDA", "is TSLA overbought on RSI", "MACD signal"

import pandas as pd, json, sys data = json.loads(sys.stdin.read()) df = pd.DataFrame(data) df = df.rename(columns={"open":"o","high":"h","low":"l","close":"c","volume":"v"}) df[["o","h","l","c","v"]] = df[["o","h","l","c","v"]].apply(pd.to_numeric) votes = {} # EMA helper def ema(s, n): return s.ewm(span=n, adjust=False).mean() # --- MACD (12, 26, 9) --- ema12 = ema(df["c"], 12); ema26 = ema(df["c"], 26) macd = ema12 - ema26; signal = ema(macd, 9); hist = macd - signal votes["MACD"] = +1 if hist.iloc[-1] > 0 and hist.iloc[-1] > hist.iloc[-2] else ( -1 if hist.iloc[-1] < 0 and hist.iloc[-1] < hist.iloc[-2] else 0) # --- RSI (14) --- delta = df["c"].diff(); gain = delta.clip(lower=0); loss = (-delta).clip(lower=0) avg_g = gain.ewm(alpha=1/14, adjust=False).mean() avg_l = loss.ewm(alpha=1/14, adjust=False).mean() rsi = 100 - 100 / (1 + avg_g / avg_l.replace(0, 1e-9)) rsi_last = rsi.iloc[-1] votes["RSI"] = -1 if rsi_last > 70 else (+1 if rsi_last < 30 else 0) # --- KDJ (9, 3, 3) --- low9 = df["l"].rolling(9).min(); high9 = df["h"].rolling(9).max() rsv = (df["c"] - low9) / (high9 - low9 + 1e-9) * 100 K = rsv.ewm(alpha=1/3, adjust=False).mean() D = K.ewm(alpha=1/3, adjust=False).mean() J = 3*K - 2*D votes["KDJ"] = +1 if J.iloc[-1] < 20 else (-1 if J.iloc[-1] > 80 else 0) # --- Bollinger Bands (20, 2) --- mid = df["c"].rolling(20).mean(); std = df["c"].rolling(20).std() upper_bb = mid + 2*std; lower_bb = mid - 2*std c_last = df["c"].iloc[-1] votes["Bollinger"] = +1 if c_last < lower_bb.iloc[-1] else ( -1 if c_last > upper_bb.iloc[-1] else 0) # --- EMA cross (50 / 200) --- e50 = ema(df["c"], 50); e200 = ema(df["c"], 200) votes["EMA_cross"] = +1 if e50.iloc[-1] > e200.iloc[-1] else -1 # --- ADX (14) --- tr = pd.concat([df["h"]-df["l"], (df["h"]-df["c"].shift()).abs(), (df["l"]-df["c"].shift()).abs()], axis=1).max(axis=1) dm_plus = (df["h"]-df["h"].shift()).clip(lower=0) dm_minus = (df["l"].shift()-df["l"]).clip(lower=0) atr14 = tr.ewm(alpha=1/14, adjust=False).mean() di_plus = 100 * dm_plus.ewm(alpha=1/14, adjust=False).mean() / atr14 di_minus = 100 * dm_minus.ewm(alpha=1/14, adjust=False).mean() / atr14 dx = (di_plus - di_minus).abs() / (di_plus + di_minus + 1e-9) * 100 adx = dx.ewm(alpha=1/14, adjust=False).mean() # ADX > 25 confirms trend; direction from DI cross votes["ADX"] = +1 if adx.iloc[-1] > 25 and di_plus.iloc[-1] > di_minus.iloc[-1] else ( -1 if adx.iloc[-1] > 25 and di_minus.iloc[-1] > di_plus.iloc[-1] else 0) # --- OBV --- obv = (df["v"] * df["c"].diff().apply(lambda x: 1 if x > 0 else (-1 if x < 0 else 0))).cumsum() votes["OBV"] = +1 if obv.iloc[-1] > obv.iloc[-5] else (-1 if obv.iloc[-1] < obv.iloc[-5] else 0) # --- Composite --- total = sum(votes.values()) composite = "买入/Buy" if total >= 3 else ("卖出/Sell" if total <= -3 else "持观望/Neutral") print(f"Composite vote: {total:+d} → {composite}") print(f" MACD hist={hist.iloc[-1]:.4f} vote={votes['MACD']:+d}") print(f" RSI(14)={rsi_last:.1f} vote={votes['RSI']:+d}") print(f" KDJ J={J.iloc[-1]:.1f} vote={votes['KDJ']:+d}") print(f" Bollinger vote={votes['Bollinger']:+d} (price vs bands)") print(f" EMA50/200 vote={votes['EMA_cross']:+d} (50={'above' if e50.iloc[-1]>e200.iloc[-1] else 'below'} 200)") print(f" ADX={adx.iloc[-1]:.1f} DI+={di_plus.iloc[-1]:.1f} DI-={di_minus.iloc[-1]:.1f} vote={votes['ADX']:+d}") print(f" OBV trend vote={votes['OBV']:+d}")

指标 / 指標 / Indicator	当前值 / 當前值 / Value	信号 / 訊號 / Signal
MACD	hist 值	多/空/中性
RSI(14)	数值	超卖/中性/超买
KDJ J	数值	超卖/中性/超买
Bollinger	价格位置	超卖/中性/超买
EMA 50/200	多空排列	多头/空头
ADX	趋势强度	趋势/震荡
OBV	5日趋势	流入/流出

Situation	简体回复 / 繁體回覆 / English reply
`command not found: longbridge`	请安装 longbridge-terminal / 請安裝 longbridge-terminal / Install longbridge-terminal first
stderr `not logged in` / `unauthorized`	请运行 `longbridge auth login` / 請執行 `longbridge auth login` / Run `longbridge auth login`
Other stderr	直接展示错误信息 / 直接顯示錯誤訊息 / Surface error verbatim

longbridge-technical

خيارات التثبيت

مراجعة ملفات المصدر

longbridge-technical

When to use

longbridge-technical

When to use

Workflow

CLI

Python analysis

Output

Error handling

MCP fallback

Related skills

longbridge-technical

معلومات المصدر

خيارات التثبيت

مراجعة ملفات المصدر

المزيد من هذا المستودع

المزيد من هذا المستودع

longbridge-technical

When to use

longbridge-technical

When to use

Workflow

CLI

Python analysis

Output

Error handling

MCP fallback

Related skills