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scanner-pmcc

@staskh · 收录于 1 周前

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.

适合你,如果做期权交易,想快速找到PMCC候选标的。

/ 下载安装
scanner-pmcc.skill双击,或拖进 Claude 桌面版 / Cowork,即完成安装↓ .skill↓ .zip
用别的 agent?下载 .zip 解压,把文件夹放进它的技能目录
Claude Code~/.claude/skills/(项目级 .claude/skills/)
Codex CLI~/.codex/skills/
Cursor自动读取上面两处目录
其他工具见其文档的「skills」目录;两个下载是同一份文件,只是名字不同
/ 通过 npx 安装 校验哈希
npx oh-my-skill add staskh/trading_skills/scanner-pmcc
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- staskh/trading_skills/scanner-pmcc
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify staskh/trading_skills/scanner-pmcc
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
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怎么用

技能原文 SKILL.md作者撰写 · MIT · cc30858

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 (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 < 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 |

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 <name>_delta (float) + <name> (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 ```
  1. Read the JSON output.
  1. 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.
  1. Save the generated markdown to sandbox/PMCC_Scan_YYYY-MM-DD_HHmm.md (match the JSON timestamp).
  1. Display the full report to the user.
Examples
# 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.

按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

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