PMCC stands for Poor Man's Covered Call: you buy a deep in-the-money LEAPS call (delta ~0.80) and sell a short-term OTM call (delta ~0.20) against it, creating a cheaper proxy for a covered call.

What makes a good PMCC candidate?

A good candidate has LEAPS delta near 0.80, a short-delta near 0.20, strong liquidity (volatility and open interest), tight spreads, IV in the 25–50% range, and a favorable annual yield.

What output does the scanner provide?

The scanner returns a JSON object with criteria (scan parameters), results (symbol, price, iv_pct, pmcc_score, leaps, short, metrics), and errors for symbols with insufficient data.

scanner-pmcc

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npx machina-cli add skill staskh/trading_skills/scanner-pmcc --openclaw

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SKILL.md

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PMCC Scanner

Finds optimal Poor Man's Covered Call setups by scoring symbols on option chain quality.

What is PMCC?

Buy deep ITM LEAPS call (delta ~0.80) + Sell short-term OTM call (delta ~0.20) against it. Cheaper alternative to covered calls.

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 [options]

Arguments

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

Scoring System (max ~11 points)

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

Output

Returns JSON with:

criteria - Scan parameters used
results - Array sorted by score:
- symbol, price, iv_pct, pmcc_score
- leaps - expiry, strike, delta, bid/ask, spread%, volume, OI
- short - expiry, strike, delta, bid/ask, spread%, volume, OI
- metrics - net_debit, short_yield%, annual_yield%, capital_required
errors - Symbols that failed (no options, insufficient data)

Examples

# Scan specific symbols
uv run python scripts/scan.py AAPL,MSFT,GOOGL,NVDA

# 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

# Save results
uv run python scripts/scan.py AAPL,MSFT,GOOGL --output pmcc_results.json

Key Constraints

Short strike must be above LEAPS strike
Options with bid = 0 (illiquid) are skipped
Moderate IV (25-50%) scores highest

Interpretation

Score > 9: Excellent candidate
Score 7-9: Good candidate
Score 5-7: Acceptable with caveats
Score < 5: Poor liquidity or structure

Dependencies

numpy
pandas
scipy
yfinance

Source

git clone https://github.com/staskh/trading_skills/blob/main/.claude/skills/scanner-pmcc/SKILL.mdView on GitHub

Overview

This tool scans symbols to assess Poor Man's Covered Call (PMCC) suitability by evaluating LEAPS and short calls across delta accuracy, liquidity, spread, IV, and yield. It ranks candidates with a score and outputs structured data to guide PMCC or diagonal-spread exploration.

How This Skill Works

It targets LEAPS delta around 0.80 and short call delta around 0.20, then scores each symbol across Delta Accuracy, Liquidity, Spread, IV Level, and Yield. The output includes criteria, a sorted results array, and any errors, with constraints such as short strike above LEAPS strike and skipping illiquid bids. Moderate IV (25–50%) is favored to maximize PMCC viability.

When to Use It

When you want PMCC candidates for a given set of symbols or a watchlist.
When exploring diagonal spreads or LEAPS-based strategies that pair a long call with a near-term short call.
When you need a data-driven ranking of PMCC setups across multiple symbols.
When evaluating liquidity, spreads, and IV to filter out illiquid or poorly structured opportunities.
When you want to validate data quality and identify symbols with insufficient option-chain data.

Quick Start

Step 1: uv run python scripts/scan.py AAPL,MSFT
Step 2: uv run python scripts/scan.py AAPL,MSFT --min-leaps-days 270 --leaps-delta 0.80 --short-delta 0.20
Step 3: Review the output JSON (criteria, results, errors) and select high-scoring PMCC candidates for deeper analysis

Best Practices

Set explicit delta targets (LEAPS ~0.80, short ~0.20) and use the defaults or adjust as needed for your risk tolerance.
Require minimum LEAPS days (default 270) to ensure a true long-dated leg.
Ensure the short strike is above the LEAPS strike and that both legs have non-zero bid to indicate liquidity.
Prioritize IV in the 25–50% range to maximize scoring while avoiding extreme IV extremes.
Sort results by pmcc_score and review any symbols in the 5–9 range for caveats before trading.

Example Use Cases

AAPL: LEAPS 9–12 months delta ~0.80 and short call delta ~0.20, high liquidity, IV ~30–45%, pmcc_score > 9.
MSFT: Strong PMCC candidate with tight LEAPS spread and short call spread under 10%.
GOOGL: PMCC candidate with favorable yield and IV; short strike remains above LEAPS strike.
TSLA: Data gaps or bid=0 in some series cause errors; scanner filters these out for clean results.
NVDA: IV around 30–40% and yields above threshold, resulting in a high pmcc_score.

Frequently Asked Questions

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