Trading_skills 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.

install

source · Clone the upstream repo

git clone https://github.com/staskh/trading_skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/staskh/trading_skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/.claude/skills/scanner-bullish" ~/.claude/skills/staskh-trading-skills-scanner-bullish && rm -rf "$T"

manifest: .claude/skills/scanner-bullish/SKILL.md

source content

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 ~8 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
	<30 (oversold)	+0.25
MACD	MACD > Signal	+1.0
	Histogram rising	+0.5
ADX	>25 with +DI > -DI	+1.5
	+DI > -DI only	+0.5
Momentum	3mo 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
```
,
```
adx
```
,
```
dmp
```
,
```
dmn
```
```
signals
```
- List of triggered conditions

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
```