Agent SkillsAlphaGBM/skills › alphagbm-hedge-advisor

alphagbm-hedge-advisor

GitHub

根据股票代码、成本价和持仓目的,自动分类持有场景(如下跌、抄底、获利保护),并从实时期权链返回具体的对冲策略建议及定价。

skills/alphagbm-hedge-advisor/SKILL.md AlphaGBM/skills

Trigger Scenarios

hedge my AAPL protect my NVDA gains collar strategy MSFT long put for TSLA how to hedge falling knife COIN reduce risk BABA lock in gains META downside protection portfolio hedge insurance for position

Install

npx skills add AlphaGBM/skills --skill alphagbm-hedge-advisor -g -y
More Options

Use without installing

npx skills use AlphaGBM/skills@alphagbm-hedge-advisor

指定 Agent (Claude Code)

npx skills add AlphaGBM/skills --skill alphagbm-hedge-advisor -a claude-code -g -y

安装 repo 全部 skill

npx skills add AlphaGBM/skills --all -g -y

预览 repo 内 skill

npx skills add AlphaGBM/skills --list

SKILL.md

Frontmatter
{
    "name": "alphagbm-hedge-advisor",
    "globs": [
        "mock-data\/hedge-advisor\/**"
    ],
    "description": "Scenario-driven hedge recommendations for an existing stock position. Takes\nticker + cost basis + purpose, auto-classifies the holding situation (falling\nknife \/ bottom-fishing \/ gain-protection \/ normal) and returns concrete Long Put,\nCollar, or Tier-down recommendations with live strikes and premiums from the\ncurrent option chain.\nTriggers: \"hedge my AAPL\", \"protect my NVDA gains\", \"collar strategy MSFT\",\n\"long put for TSLA\", \"how to hedge falling knife COIN\", \"reduce risk BABA\",\n\"lock in gains META\", \"downside protection\", \"portfolio hedge\", \"insurance for position\"\n"
}

AlphaGBM Hedge Advisor

"I own AAPL at $140 and it's now $180 — how do I protect the gains?"

Takes that question literally. Given a ticker + cost basis + position purpose, the skill classifies the holding into one of four scenarios and returns ready-to-trade hedge specs with strikes and costs already resolved from the live option chain.

Scenarios

Scenario Trigger Recommended Hedge
Falling Knife Recent drawdown ≥ 15% from 30-day high AND PnL ≤ +5% Long Put 5% OTM, 75 DTE, 100% cover, budget ~5%
Bottom Fishing PnL within ±8% of cost AND purpose = just_bought or long_term Long Put 5% OTM, 90 DTE, 50-75% cover, budget ~3%
Gain Protection PnL ≥ 15% Collar 95/110 (zero-cost or net-credit) + Tier-down as alternative
Normal Hold Fallback when no scenario fires Position rules only, no urgent hedge

What's Returned

For each recommendation spec, the skill resolves actual strikes and prices from the live option chain:

  • Long Put: strike, DTE, cost_per_share, cost_per_contract, cost_pct_of_spot, delta, IV
  • Collar: long_put_strike, short_call_strike, put_cost, call_credit, net_cost_per_share (negative = you receive a credit), breakeven analysis
  • Tier-down / Position rules: static rules copy only

Also returns a position_rules[] array (single-name ≤20%, sector ≤30-35%, cash reserve 10-15%, etc.) for the normal-hold case.

How to Use

Input:

  • ticker (required)
  • cost_basis (required, float — your average entry price)
  • purpose (optional, default long_term) — one of long_term / short_term / pre_earnings / just_bought

Output:

  • Scenario label + reason (zh/en)
  • Current price, cost basis, unrealized P&L %, recent drawdown %
  • recommendations[] — each with type, priority, title, rationale, and resolved block containing the actual priced hedge
  • position_rules[] — always-applicable sizing rules

Example Queries:

  • hedge my AAPL at $140, now it's $180 → Gain Protection → Collar 95/110 quote
  • I just bought NVDA at $110 on the dip, should I hedge? → Falling Knife or Bottom Fishing → Long Put 5% OTM 60-90 DTE
  • how to protect my TSLA position → Gain Protection or Bottom Fishing based on PnL
  • collar MSFT at cost 340 current 410 → Full collar pricing

Mock Data

Mock responses in mock-data/hedge-advisor/ — sample across all four scenarios.

API Endpoint

GET /api/options/hedge-advisor?ticker={SYMBOL}&cost_basis={PRICE}&purpose={PURPOSE}

Query params:

  • ticker (required)
  • cost_basis (required, float > 0)
  • purpose (default long_term) — one of long_term / short_term / pre_earnings / just_bought

Response shape:

{
  "success": true,
  "ticker": "AAPL",
  "current_price": 180.0,
  "cost_basis": 140.0,
  "unrealized_pnl_pct": 28.57,
  "recent_drawdown_pct": 3.1,
  "purpose": "long_term",
  "scenario": {
    "scenario": "gain_protection",
    "label_zh": "浮盈怕坐电梯",
    "label_en": "Gain Protection",
    "reason_zh": "已浮盈 28.6%,需要保护已实现收益。",
    "reason_en": "Up 28.6% on cost — protect unrealized gains.",
    "unrealized_pnl_pct": 28.57
  },
  "recommendations": [
    {
      "type": "collar",
      "priority": 1,
      "title_zh": "Collar 95/110 锁定收益",
      "title_en": "Collar 95/110 lock-in",
      "rationale_zh": "...",
      "rationale_en": "...",
      "resolved": {
        "long_put_strike": 170.0,
        "short_call_strike": 200.0,
        "put_cost": 2.15,
        "call_credit": 2.45,
        "net_cost_per_share": -0.30,
        "net_cost_per_contract": -30,
        "is_credit": true,
        "dte": 62
      }
    },
    {"type": "tier_down", "priority": 2, ...}
  ],
  "position_rules": [
    {"rule_zh": "单票仓位 ≤ 20%", "rule_en": "Single ticker ≤20%", ...},
    ...
  ]
}

Pricing: 1 option-analysis credit per call; 5-min cache per (ticker, cost_basis, purpose).

Related Skills

Skill Relevance
alphagbm-options-strategy Multi-leg strategy builder (for custom hedges beyond presets)
alphagbm-greeks Greeks of the resulting hedge position
alphagbm-pnl-simulator Stress-test the hedge at various future prices

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Version History

  • c69fa1b Current 2026-07-05 20:18

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Hash
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Indexed
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