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Scanner Bullish

skill-staskh-trading-skills-scanner-bullish · by staskh

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.

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Install

$ agentstack add skill-staskh-trading-skills-scanner-bullish

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Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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Reliability & compatibility

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1mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

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)

| Indicator | Condition | Points | |-----------|-----------|--------| | SMA20 | Price > SMA20 | +1.0 | | SMA50 | Price > SMA50 | +1.0 | | RSI | 50-70 (bullish) | +1.0 | | | 30-50 (neutral) | +0.5 | | | Signal | +1.0 | | | Histogram rising | +0.5 | | EMA9/21 | EMA9 > EMA21 (golden cross) | +0.5 | | | EMA9 25 with +DI > -DI | +1.5 | | | +DI > -DI only | +0.5 | | Momentum | period 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.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.