// Scan stocks for Poor Man's Covered Call (PMCC) suitability. Analyzes LEAPS and short call options for delta, liquidity, spread, IV, yield, trend direction, and earnings proximity. Use when user asks about PMCC candidates, diagonal spreads, or LEAPS strategies.
| name | scanner-pmcc |
| description | Scan stocks for Poor Man's Covered Call (PMCC) suitability. Analyzes LEAPS and short call options for delta, liquidity, spread, IV, yield, trend direction, and earnings proximity. Use when user asks about PMCC candidates, diagonal spreads, or LEAPS strategies. |
| dependencies | ["trading-skills"] |
Finds optimal Poor Man's Covered Call setups by scoring symbols on option chain quality.
Buy deep ITM LEAPS call (delta ~0.80) + Sell short-term OTM call (delta ~0.20) against it. Cheaper alternative to covered calls.
Note: If
uvis not installed orpyproject.tomlis not found, replaceuv run pythonwithpythonin all commands below.
uv run python scripts/scan.py SYMBOLS [options]
SYMBOLS - Comma-separated tickers or path to JSON file from bullish scanner--min-leaps-days - Minimum LEAPS expiration in days (default: 270 = 9 months)--leaps-delta - Target LEAPS delta (default: 0.80)--short-delta - Target short call delta (default: 0.20)--output - Save results to JSON file (use this; Claude generates the report from the JSON)--report - Save auto-generated markdown to file (programmatic fallback only — prefer Claude-generated reports)| Category | Condition | Points |
|---|---|---|
| Delta Accuracy | LEAPS within ±0.05 | +2 |
| LEAPS within ±0.10 | +1 | |
| Short within ±0.05 | +1 | |
| Short within ±0.10 | +0.5 | |
| Liquidity | LEAPS vol+OI > 100 | +1 |
| LEAPS vol+OI > 20 | +0.5 | |
| Short vol+OI > 500 | +1 | |
| Short vol+OI > 100 | +0.5 | |
| Spread | LEAPS spread < 5% | +1 |
| LEAPS spread < 10% | +0.5 | |
| Short spread < 10% | +1 | |
| Short spread < 20% | +0.5 | |
| IV Level | 25-50% (ideal) | +2 |
| 20-60% | +1 | |
| Yield | Annual > 50% | +2 |
| Annual > 30% | +1 | |
| Trend | Price > SMA50 | +1 / -1 |
| RSI > 50 | +0.5 / -0.5 | |
| MACD > signal | +0.5 / -0.5 | |
| Earnings | Next earnings > 45 days | +1.0 |
| Earnings within 45 days | -1.0 | |
| Earnings within short expiry | -2.0 |
Returns JSON with:
criteria - Scan parameters usedresults - Array sorted by score:
symbol, price, iv_pct, pmcc_score, max_possible_score (always 14)leaps - expiry, strike, delta, iv (calculated from bid/ask), last_price, bid/ask, spread%, volume, OIshort - expiry, strike, delta, iv (calculated from bid/ask), last_price, bid/ask, spread%, volume, OIearnings_date - next earnings date (YYYY-MM-DD) or nullmetrics - net_debit, short_yield%, annual_yield%, capital_requiredscore_breakdown - every scoring component as a <name>_delta (float) + <name> (explanation string) pair:
leaps_delta, short_delta, leaps_liquidity, short_liquidity, leaps_spread, short_spread, iv, yieldtrend_delta, trend (per-indicator dict)earnings_delta, earnings_delta values sum to pmcc_scoreerrors - Symbols that failed (no options, insufficient data)When the user asks for a report, a written analysis, or a saved document:
Run the scanner with --output to capture JSON data:
uv run python scripts/scan.py SYMBOLS --output sandbox/PMCC_Scan_YYYY-MM-DD_HHmm.json
Read the JSON output.
Generate the markdown report yourself using the template defined in templates/markdown-template.md. Do not use the --report flag — that produces mechanical string output. Claude-generated reports include real analysis, contextual warnings, and trader-relevant narrative.
Save the generated markdown to sandbox/PMCC_Scan_YYYY-MM-DD_HHmm.md (match the JSON timestamp).
Display the full report to the user.
# Scan specific symbols
uv run python scripts/scan.py AAPL,MSFT,GOOGL,NVDA
# Scan and save JSON for report generation
uv run python scripts/scan.py AAPL,MSFT,GOOGL --output sandbox/PMCC_Scan_2026-01-15_1430.json
# Use output from bullish scanner
uv run python scripts/scan.py bullish_results.json
# Custom delta targets
uv run python scripts/scan.py AAPL,MSFT --leaps-delta 0.70 --short-delta 0.15
# Longer LEAPS (1 year minimum)
uv run python scripts/scan.py AAPL,MSFT --min-leaps-days 365
IV is always computed from market price data via Black-Scholes, never taken from Yahoo Finance's impliedVolatility column:
This applies to both compute_atm_iv (used for scanner baseline IV) and per-option delta calculations.
max_possible_score is always 14 — use pmcc_score / max_possible_score to gauge how close a candidate is to perfectnumpypandasscipyyfinanceAll 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.
Convert a markdown file to PDF using mistune + reportlab. Use when the user wants to convert a .md file to PDF, or when another skill needs to produce a PDF from markdown output.
Generate comprehensive stock analysis report (PDF or markdown) with trend, PMCC, and fundamental analysis
Downside stop-loss management for PMCC, naked LEAPS, and stock positions in IB. Computes stop prices, detects alerts, and places conditional combo orders. Dry-run by default. Requires TWS or IB Gateway running locally.
Fetch trade executions from Interactive Brokers filtered by account, date range, or symbol. Supports live API (~7 days history) and FlexReport (full history). Use when user asks about their trades, executions, or transaction history. Requires TWS or IB Gateway running locally.
Analyze PMCC (Poor Man's Covered Call / diagonal spread) positions from IB portfolio. For each diagonal spread, reports short leg risk (delta, IV, assignment probability), daily P&L projections, top-3 roll candidates, and a side-by-side comparison table. Requires TWS or IB Gateway running locally.
Get upcoming earnings dates with timing (before/after market) and EPS estimates. Use when user asks about earnings dates, earnings calendar, when a company reports, or upcoming earnings.