# Scanner Pmcc

> 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.

- **Type:** Skill
- **Install:** `agentstack add skill-staskh-trading-skills-scanner-pmcc`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [staskh](https://agentstack.voostack.com/s/staskh)
- **Installs:** 0
- **Category:** [Finance & Payments](https://agentstack.voostack.com/c/finance-and-payments)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [staskh](https://github.com/staskh)
- **Source:** https://github.com/staskh/trading_skills/tree/main/.claude/skills/scanner-pmcc

## Install

```sh
agentstack add skill-staskh-trading-skills-scanner-pmcc
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# 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.

```bash
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 (use this; Claude generates the report from the JSON)
- `--report` - Save auto-generated markdown to file (programmatic fallback only — prefer Claude-generated reports)

## Scoring System (max possible: 14, range: -4 to 14)

| 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  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 |

## Output

Returns JSON with:
- `criteria` - Scan parameters used
- `results` - 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, OI
  - `short` - expiry, strike, delta, **iv** (calculated from bid/ask), **last_price**, bid/ask, spread%, volume, OI
  - `earnings_date` - next earnings date (YYYY-MM-DD) or null
  - `metrics` - net_debit, short_yield%, annual_yield%, capital_required
  - `score_breakdown` - every scoring component as a `_delta` (float) + `` (explanation string) pair:
    - Base: `leaps_delta`, `short_delta`, `leaps_liquidity`, `short_liquidity`, `leaps_spread`, `short_spread`, `iv`, `yield`
    - Trend: `trend_delta`, `trend` (per-indicator dict)
    - Earnings: `earnings_delta`, `earnings`
    - All `_delta` values sum to `pmcc_score`
- `errors` - Symbols that failed (no options, insufficient data)

## Report Generation

When the user asks for a report, a written analysis, or a saved document:

1. Run the scanner with `--output` to capture JSON data:
   ```bash
   uv run python scripts/scan.py SYMBOLS --output sandbox/PMCC_Scan_YYYY-MM-DD_HHmm.json
   ```

2. Read the JSON output.

3. 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.

4. Save the generated markdown to `sandbox/PMCC_Scan_YYYY-MM-DD_HHmm.md` (match the JSON timestamp).

5. Display the full report to the user.

## Examples

```bash
# 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 Calculation

IV is always computed from market price data via Black-Scholes, never taken from Yahoo Finance's `impliedVolatility` column:

- **During trading hours**: IV derived from bid/ask mid price
- **Off-hours (bid=ask=0)**: IV derived from last price, using the option's last trade timestamp as the pricing moment (not current wall-clock time)

This applies to both `compute_atm_iv` (used for scanner baseline IV) and per-option delta calculations.

## Key Constraints

- Short strike **must be above** LEAPS strike
- Options with bid = 0 and no last price are skipped
- Moderate IV (25-50%) scores highest

## Interpretation

- Score > 12: Excellent candidate (strong structure + bullish trend + clear earnings runway)
- Score 10-12: Good candidate
- Score 6-10: Acceptable with caveats
- Score < 6: Poor structure, bearish trend, or earnings risk
- `max_possible_score` is always 14 — use `pmcc_score / max_possible_score` to gauge how close a candidate is to perfect

## Dependencies

- `numpy`
- `pandas`
- `scipy`
- `yfinance`

## 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](https://github.com/staskh)
- **Source:** [staskh/trading_skills](https://github.com/staskh/trading_skills)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-staskh-trading-skills-scanner-pmcc
- Seller: https://agentstack.voostack.com/s/staskh
- Browse the marketplace: https://agentstack.voostack.com/browse

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