longbridge-ichimoku

name	longbridge-ichimoku
description	Ichimoku Cloud (一目均衡表) five-line system signal engine for stocks listed in HK / US / A-share / Singapore via Longbridge Securities. Computes Tenkan-sen, Kijun-sen, Senkou Span A/B, and Chikou Span from OHLCV data; generates price-vs-cloud position, line-cross signals, and full trend-confirmation scores. Triggers: "一目均衡表", "一目云", "云图", "转折线", "基准线", "先行带", "迟行线", "云上", "云下", "一目均衡表", "一目雲", "雲圖", "轉折線", "基準線", "先行帶", "遲行線", "ichimoku", "ichimoku cloud", "tenkan sen", "kijun sen", "senkou span", "chikou span", "cloud breakout".
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-ichimoku

Computes the full Ichimoku Cloud five-line system from 200 days of OHLCV data and produces bullish / bearish / neutral signals with per-component interpretation.

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

When to use

• "NVDA 一目云位置", "700.HK 是否在云上方", "转折线有没有上穿基准线"
• "TSLA ichimoku signal", "is AAPL above the cloud", "cloud breakout"
• "600519.SH 雲圖分析", "先行帶是否扩张", "遲行線確認"

Workflow

1. Resolve the symbol to <CODE>.<MARKET> format.
2. Fetch 200 daily candles (need ≥ 52 bars for Senkou Span B):

   longbridge kline <SYMBOL> --period day --count 200 --format json
   

3. Run the Python analysis below to compute all five lines and derive signals.
4. Report each component's value and signal, then summarise with a composite conclusion.

CLI

longbridge kline NVDA.US   --period day --count 200 --format json
longbridge kline 700.HK    --period day --count 200 --format json
longbridge kline 600519.SH --period day --count 200 --format json

Run longbridge kline --help to verify current flag names and defaults.

Python analysis

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)
df = df.reset_index(drop=True)

def midpoint(h, l, n):
    return (h.rolling(n).max() + l.rolling(n).min()) / 2

# --- Five lines ---
tenkan  = midpoint(df["h"], df["l"], 9)           # 转折线 / 轉折線 / Tenkan-sen
kijun   = midpoint(df["h"], df["l"], 26)           # 基准线 / 基準線 / Kijun-sen
span_a  = ((tenkan + kijun) / 2).shift(26)         # 先行带A (shifted forward 26)
span_b  = midpoint(df["h"], df["l"], 52).shift(26) # 先行带B (shifted forward 26)
chikou  = df["c"].shift(-26)                        # 迟行线 (shifted back 26)

i = (df) -   
c_now   = df[].iloc[i]
t_now   = tenkan.iloc[i]
k_now   = kijun.iloc[i]
sa_now  = span_a.iloc[i]
sb_now  = span_b.iloc[i]

chikou_ref = df[].iloc[i - ]  i >=   

cloud_top    = (sa_now, sb_now)  pd.notna(sa_now)  pd.notna(sb_now)  
cloud_bottom = (sa_now, sb_now)  pd.notna(sa_now)  pd.notna(sb_now)  

signals = []


 cloud_top  c_now > cloud_top:
    signals.append((, +))
 cloud_bottom  c_now < cloud_bottom:
    signals.append((, -))
:
    signals.append((, ))


 pd.notna(t_now)  pd.notna(k_now):
    t_prev = tenkan.iloc[i-]; k_prev = kijun.iloc[i-]
     t_now > k_now  t_prev <= k_prev:
        signals.append((, +))
     t_now < k_now  t_prev >= k_prev:
        signals.append((, -))
     t_now > k_now:
        signals.append((, +))
    :
        signals.append((, -))


 pd.notna(sa_now)  pd.notna(sb_now):
     sa_now > sb_now:
        signals.append((, +))
    :
        signals.append((, -))


 chikou_ref     pd.notna(chikou_ref):
    chikou_now = df[].iloc[i]  
     chikou_now > chikou_ref:
        signals.append((, +))
    :
        signals.append((, -))


 pd.notna(t_now)  c_now > t_now:
    signals.append((, +))
 pd.notna(k_now)  c_now > k_now:
    signals.append((, +))

total = (s  _, s  signals)
composite =   total >=   (
                         total >=   (
                         total <= -  (
              total <= -  )))

()
()
()
(  pd.notna(sa_now)  )
(  pd.notna(sb_now)  )
(  cloud_top  )
()
 label, s  signals:
    ()

Output

Report the five line values and signal table, then a composite conclusion. Example structure:

指标 / 指標 / Component	值 / 值 / Value	信号 / 訊號 / Signal
转折线 Tenkan-sen	数值	—
基准线 Kijun-sen	数值	—
先行带 A Senkou A	数值	—
先行带 B Senkou B	数值	云色
迟行线 Chikou Span	当前收盘	确认多/空
价格 vs 云	高于/低于/在内	+2 / -2 / 0
综合信号	—	看多/看空/中性

Cite Longbridge Securities / 数据来源:长桥证券 / 數據來源:長橋證券.

Error handling

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
Fewer than 52 bars returned	告知数据不足，需要至少 52 根 K 线 / 需至少 52 根 K 線 / Need at least 52 bars for Senkou B
Other stderr	直接展示错误信息 / 直接顯示錯誤訊息 / Surface error verbatim

MCP fallback

When the CLI is unavailable, fall back to the MCP server. Discover available tools from the MCP server's tool list at runtime.

Related skills

• longbridge-kline — raw OHLCV data and charting
• longbridge-technical — MACD / RSI / KDJ / Bollinger indicator signals
• longbridge-candlestick — K-line pattern recognition
• longbridge-capital-flow — intraday capital-flow signals