Install
$ agentstack add skill-staskh-trading-skills-scanner-bullish ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo 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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Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →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 scansymbols_scanned- Total symbols analyzedresults- Array sorted by score (highest first):symbol,score,pricenext_earnings,earnings_timing(BMO/AMC)period_return_pct,pct_from_sma20,pct_from_sma50rsi,macd,macd_signal,macd_hist,adx,dmp,dmnema9,ema21— current EMA9 and EMA21 valuesema_crossover- Most recent EMA9/EMA21 crossover (ornullif 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 (ornullif 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 smalldays_ago(0-5): fresh bullish crossover — early entry signaldirection: "up"from a deeply negative signal: recovery from correctiondirection: "down": momentum has turned bearish regardless of scorenull: 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
pandaspandas-tayfinance
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.
- Author: staskh
- Source: staskh/trading_skills
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.