| name | options-flow-scanner |
| description | Scan for unusual options activity and large institutional options flow. Identifies calls/puts with abnormal volume vs open interest ratios, sweeps, and block trades. Use when user asks about options flow, unusual options activity, dark pool options, smart money options bets, or wants to track what institutions are buying in the options market. |
Options Flow Scanner
Identify unusual options activity โ high volume/OI ratio, sweeps, and large block trades โ as signals of institutional positioning.
When to Use
- User asks for unusual options activity or options flow
- User wants to know what smart money is betting on via options
- User requests call/put sweep detection or block trade analysis
- User wants options-based confirmation for a directional trade thesis
Prerequisites
yfinance Python package (pip install yfinance) โ no API key required
Workflow
Step 1: Run the Scanner
python3 skills/options-flow-scanner/scripts/scan_options_flow.py \
--symbols AAPL NVDA MSFT TSLA META \
--output-dir reports/
python3 skills/options-flow-scanner/scripts/scan_options_flow.py \
--symbols AAPL NVDA \
--min-volume 500 \
--min-oi-ratio 3.0 \
--output-dir reports/
Step 2: Interpret Results
For each flagged contract:
- Volume/OI Ratio > 3x: Unusual interest relative to existing open interest
- Sweep flag: Multi-exchange split orders indicate urgency (institutional)
- Put/Call ratio: < 0.7 bullish skew, > 1.3 bearish skew
- Days to expiry: < 7 DTE = speculative; 30โ90 DTE = directional conviction
Step 3: Cross-Reference
- Load
references/options_flow_interpretation.md for sweep vs block trade context
- Confirm underlying chart trend using Technical Analyst skill
- Check earnings dates โ flow before earnings is often hedging, not directional
Output
options_flow_YYYY-MM-DD.json โ Flagged contracts with metadataoptions_flow_YYYY-MM-DD.md โ Human-readable ranked flow table
Resources
references/options_flow_interpretation.md โ Sweep/block/dark pool interpretation guide
