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Alphagbm Options Score

核心功能:采用多因子模型(含流动性、IV吸引力、风险收益等),针对4种期权策略为合约打分(0-100分分级),输出得分拆解、风险收益profile等。典型场景:评估期权标的、筛选最优行权价/到期日、排名优质合约。输入为标的代码及查询指令,支持多种API调用方式,提供免费额度与模拟测试数据。

clementgu
clementgu
热度 13.89
最近更新 2026-07-23 14:14:44
分类:数据依赖:第三方 API / 读写文件 / 内部调用大模型应用场景:财务 / 数据处理 / 报告撰写

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add alphagbm-options-score
Metadata
name
alphagbm-options-score
description
Score and rank options contracts for any ticker using AlphaGBM's multi-factor scoring model (liquidity, IV attractiveness, Greeks balance, risk/reward). Returns scored option chains with the best contracts highlighted. Use when: evaluating which option to trade, finding the best strike/expiry, ranking options by quality. Triggers on: "score AAPL options", "best options for NVDA", "which TSLA call should I buy", "option chain for SPY", "rank META puts".
globs
["mock-data/*.json"]

AlphaGBM Options Score

Prerequisites

  • API Key: Set env ALPHAGBM_API_KEY (format agbm_xxxx...).
  • Base URL: Default https://alphagbm.zeabur.app. Override with env ALPHAGBM_BASE_URL.

What This Skill Does

Scores every option contract in a chain using a multi-factor model across 4 strategy types, so you instantly know which contracts have the best risk/reward profile.

Strategy Scoring Models

Sell Put Weights

Factor Weight Description
premium_yield 20% Annualized return from premium
support_strength 20% Proximity to key support levels
safety_margin 15% ATR-adjusted OTM buffer
trend_alignment 15% Downtrend = 100, Uptrend = 30
probability_profit 15% Black-Scholes prob of expiring OTM
liquidity 10% Volume + OI + spread
time_decay 5% 20-45 DTE optimal

Sell Call Weights

Factor Weight
premium_yield 20%
resistance_strength 20%
trend_alignment 15%
upside_buffer 15%
liquidity 10%
is_covered 10%
time_decay 5%
overvaluation 5%

Buy Call Weights

Factor Weight
bullish_momentum 25%
breakout_potential 20%
value_efficiency 20%
volatility_timing 15%
liquidity 10%
time_optimization 10%

Buy Put Weights

Factor Weight
bearish_momentum 25%
support_break 20%
value_efficiency 20%
volatility_expansion 15%
liquidity 10%
time_value 10%

Score Scale

  • 80-100: Exceptional — top-tier opportunity
  • 60-79: Strong — good trade candidate
  • 40-59: Average — proceed with caution
  • 0-39: Poor — avoid unless hedging

Risk-Return Profiles

Style Typical Win Rate Typical Return
steady_income 65-80% 1-5%/month
balanced 40-55% 50-200%
high_risk_high_reward 20-40% 2-10x
hedge 30-50% 0-1x

API Endpoints

Get Option Expirations

GET /api/options/expirations/<SYMBOL>

Option Chain Analysis -- Synchronous

POST /api/options/chain-sync
Content-Type: application/json

{"symbol": "AAPL", "expiry_date": "2026-04-17"}

Add ?compact=true for condensed response.

Response includes for each of 4 strategies (Sell Put, Sell Call, Buy Call, Buy Put):

  • Top 10 recommendations sorted by score (0-100)
  • Score breakdown: premium_yield, support/resistance_strength, safety_margin, trend_alignment, probability_profit, liquidity, time_decay
  • ATR safety info (safety_ratio, atr_multiples, is_safe)
  • Risk-return profile: style, risk_level, win_probability
  • Trend analysis: direction, strength, alignment score

Option Chain Analysis -- Async

POST /api/options/chain-async
Content-Type: application/json

{"symbol": "TSLA", "expiry_date": "2026-04-17"}

Returns {"task_id": "uuid"}. Poll with: GET /api/tasks/<task_id>.

Enhanced Single-Option Analysis -- Sync

POST /api/options/enhanced-sync
Content-Type: application/json

{"symbol": "AAPL", "option_identifier": "AAPL260417C00190000"}

Enhanced Single-Option Analysis -- Async

POST /api/options/enhanced-async
Content-Type: application/json

{"symbol": "AAPL", "option_identifier": "AAPL260417C00190000"}

Reverse Score

Score a specific contract from known parameters:

POST /api/options/reverse-score
Content-Type: application/json

{"symbol": "AAPL", "option_type": "CALL", "strike": 190, "expiry_date": "2026-02-16", "option_price": 2.50, "implied_volatility": 28}

Batch Chain Analysis

POST /api/options/chain/batch
Content-Type: application/json

{"symbols": ["AAPL", "NVDA"], "expiries": ["2026-04-17", "2026-05-15"]}

Max 3 symbols x 2 expiries per request.

IV Snapshot (instant, no quota cost)

GET /api/options/snapshot/<SYMBOL>

Returns: ATM IV, IV Rank, HV 30d, VRP, VRP level.

Daily Recommendations (no auth required)

GET /api/options/recommendations?count=5

Typical Workflow

  1. Get expirations: GET /api/options/expirations/AAPL
  2. Quick IV check: GET /api/options/snapshot/AAPL (free, no quota)
  3. Run chain analysis: POST /api/options/chain-sync with symbol + expiry
  4. Drill into a specific contract: POST /api/options/enhanced-sync with option_identifier
  5. Compare across tickers: POST /api/options/chain/batch for multi-symbol analysis

Quota

  • Free: 1 options analysis/day
  • Plus: 1,000/month
  • Pro: 5,000/month
  • Snapshot and recommendations endpoints cost nothing.

Output Formatting Tips

  • Scores are 0-100; present top picks in a table sorted by score descending.
  • Always show the score breakdown factors so users understand why a contract scored well.
  • Highlight ATR safety info (is_safe flag) prominently for sell strategies.
  • Include the risk-return style label (steady_income, balanced, etc.) for quick context.

Example Queries

User Says What Happens
"Score AAPL options" Full chain with scores, top picks highlighted
"Best NVDA call to buy" Filtered to calls, sorted by score descending
"TSLA puts for next Friday" Filtered by expiry + type
"Which SPY option has the best risk/reward?" Sorted by risk_reward factor

Mock Data

Demo tickers available without API key: AAPL, NVDA, SPY, TSLA, META. Uses realistic option chain snapshots from mock-data/.

Related Skills

  • alphagbm-stock-analysis -- Analyze the underlying stock first
  • alphagbm-options-strategy -- Build multi-leg strategies with top-scored contracts
  • alphagbm-greeks -- Deep-dive into Greeks for a specific contract
  • alphagbm-vol-surface -- See if IV is cheap or expensive across strikes

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