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scanner-pmcc扫描仪 PMCC

Agent Skill

scanner-pmcc 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

659

周安装

28

GitHub Stars

131

下载量

231
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:scanner-pmcc(扫描仪 PMCC)
来源仓库:https://github.com/staskh/trading_skills
仓库路径:skills/scanner-pmcc
安装命令:
npx skills add https://github.com/staskh/trading_skills --skill scanner-pmcc
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/staskh/trading_skills --skill scanner-pmcc

简介

scanner-pmcc 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 适用于根据关键词、任务场景或来源线索进行信息搜集与整理。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装使用。
  • 建议确认权限范围和维护状态,避免触发联网或文件读写操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

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 possible: 14, range: -4 to 14)

CategoryConditionPoints
Delta AccuracyLEAPS within ±0.05+2
LEAPS within ±0.10+1
Short within ±0.05+1
Short within ±0.10+0.5
LiquidityLEAPS vol+OI > 100+1
LEAPS vol+OI > 20+0.5
Short vol+OI > 500+1
Short vol+OI > 100+0.5
SpreadLEAPS spread < 5%+1
LEAPS spread < 10%+0.5
Short spread < 10%+1
Short spread < 20%+0.5
IV Level25-50% (ideal)+2
20-60%+1
YieldAnnual > 50%+2
Annual > 30%+1
TrendPrice > SMA50+1 / -1
RSI > 50+0.5 / -0.5
MACD > signal+0.5 / -0.5
EarningsNext 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, bid/ask, spread%, volume, OI - short - expiry, strike, delta, bid/ask, spread%, volume, OI - 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)

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 > 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

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

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能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

31%
按下载量换算72

Claude

30.8%
按下载量换算71

Cursor

18.92%
按下载量换算44

Gemini CLI

9.59%
按下载量换算22

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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