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scanner-bullish

scanner-bullish

Scan stocks for bullish trends using technical indicators (SMA, RSI, MACD, ADX). Use when user asks to scan for bullish stocks, find trending stocks, or rank symbols by momentum.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentación de la Skill

GitHub

name: scanner-bullish description: Scan stocks for bullish trends using technical indicators (SMA, RSI, MACD, ADX). Use when user asks to scan for bullish stocks, find trending stocks, or rank symbols by momentum. dependencies: ["trading-skills"]

Bullish Scanner

Scans symbols for bullish trends and ranks them by composite score.

Instructions

Note: If uv is not installed or pyproject.toml is not found, replace uv run python with python in all commands below.

uv run python scripts/scan.py SYMBOLS [--top N] [--period PERIOD]

Arguments

  • SYMBOLS - Comma-separated ticker symbols (e.g., AAPL,MSFT,GOOGL,NVDA)
  • --top - Number of top results to return (default: 30)
  • --period - Historical period for analysis: 1mo, 3mo, 6mo (default: 3mo)

Scoring System (max ~9.5 points)

IndicatorConditionPoints
SMA20Price > SMA20+1.0
SMA50Price > SMA50+1.0
RSI50-70 (bullish)+1.0
30-50 (neutral)+0.5
<30 (oversold)+0.25
MACDMACD > Signal+1.0
Histogram rising+0.5
EMA9/21EMA9 > EMA21 (golden cross)+0.5
EMA9 < EMA21 (death cross)-0.25
Dual crossoverBoth up, both ≤10 days+1.0
Both up, any age+0.5
Both down, both ≤10 days-1.0
Both down, any age-0.5
Directions conflict-0.5
ADX>25 with +DI > -DI+1.5
+DI > -DI only+0.5
Momentumperiod return / 20-1 to +2

Output

Returns JSON with:

  • scan_date - Timestamp of scan
  • symbols_scanned - Total symbols analyzed
  • results - Array sorted by score (highest first):
    • symbol, score, price
    • next_earnings, earnings_timing (BMO/AMC)
    • period_return_pct, pct_from_sma20, pct_from_sma50
    • rsi, macd, macd_signal, macd_hist, adx, dmp, dmn
    • ema9, ema21 — current EMA9 and EMA21 values
    • ema_crossover - Most recent EMA9/EMA21 crossover (or null if none found):
      • direction - "up" (EMA9 crossed above EMA21 = bullish) or "down" (crossed below = bearish)
      • days_ago - Trading days since the crossover bar (0 = happened in the most recent bar)
    • macd_crossover - Most recent MACD crossover (or null if none found):
      • direction - "up" (MACD crossed above signal = bullish) or "down" (crossed below = bearish)
      • days_ago - Trading days since the crossover bar (0 = happened in the most recent bar)
    • signals - List of triggered conditions

EMA Crossover Interpretation

  • EMA9 > EMA21 with small days_ago (0-5): fresh golden cross — short-term momentum confirmed
  • EMA9 just crossed below EMA21: death cross — short-term momentum turning negative
  • EMA9 crossover lagging MACD crossover by days: normal — MACD leads, EMA confirms
  • null: EMA9/21 relationship unchanged throughout the period

MACD Crossover Interpretation

  • direction: "up" with small days_ago (0-5): fresh bullish crossover — early entry signal
  • direction: "up" from a deeply negative signal: recovery from correction
  • direction: "down": momentum has turned bearish regardless of score
  • null: no sign change found in the period — trend has been consistently one-directional

Examples

# Scan a few symbols
uv run python scripts/scan.py AAPL,MSFT,GOOGL,NVDA,TSLA

# Get top 10 from larger list
uv run python scripts/scan.py AAPL,MSFT,GOOGL,NVDA,TSLA,AMD,AMZN,META --top 10

# Use 6-month lookback
uv run python scripts/scan.py AAPL,MSFT,GOOGL --period 6mo

Interpretation

  • Score > 6: Strong bullish trend
  • Score 4-6: Moderate bullish
  • Score 2-4: Neutral/weak
  • Score < 2: Bearish or no trend

Dependencies

  • pandas
  • pandas-ta
  • yfinance

Timezone

All timestamps and time-based calculations must use the America/New_York timezone. All JSON output must include generated_at (NY time string) and data_delay fields.

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