Claude Code Plugins

Community-maintained marketplace

Feedback

alphagbm-marks-cycle

@AlphaGBM/skills
726
1

|

Install Skill

Shared

Installs to .agents/skills, used by Codex, Amp, Warp, Cursor, OpenCode, and more.

CodexAmp
Warp
CursorOpenCode
Cline
Gemini CLI
GitHub Copilot
Personal

Available across projects.

$npx skills-installer add @AlphaGBM/skills/alphagbm-marks-cycle --client shared
Project

Writes to .agents/skills.

$npx skills-installer add @AlphaGBM/skills/alphagbm-marks-cycle -p --client shared
Note: Review the skill instructions before using it.

SKILL.md

name alphagbm-marks-cycle
description Howard Marks-style market cycle position 0-100, with 0 = panic bottom (hard offense) and 100 = euphoric top (hard defense). Blends VIX (40%) + SPY IV Rank (25%) + Put/Call ratio (20%) + valuation percentile (15%) into a single number and maps to an offense-vs-defense posture. Free endpoint, no auth, 5-min cache — the goal is to make "where are we in the cycle" a one-call lookup. Triggers: "where is the market in the cycle", "Howard Marks style cycle read", "am I supposed to be offensive or defensive", "is this a buying cycle", "cycle position right now", "Marks cycle score", "sentiment read for SPY"
globs mock-data/marks-cycle/**

AlphaGBM Howard Marks Cycle

"Cycles are real — the shape just isn't predictable." Howard Marks's framework rejects forecasting and replaces it with cycle-position awareness: offense when others are pessimistic, defense when others are optimistic.

This skill gives you the one number Marks's entire philosophy implies: where are we right now.

The Cycle Score

Each signal is mapped to its own cycle component 0-100, then weighted:

Signal Weight Interpretation
VIX 40% Low VIX → complacency → late cycle (high score). High VIX → fear → early cycle (low score)
IV Rank (SPY) 25% High IV rank → fear → early cycle
Put/Call ratio 20% Low P/C → complacent → late cycle
Valuation percentile 15% Higher PE percentile → later cycle

Weights renormalize when data points are missing (e.g., P/C not available).

Posture Bands

  • 0-24OFFENSE_HARD — extreme fear is opportunity. Buy aggressively.
  • 25-39OFFENSE — add, sell vol (short premium).
  • 40-59NEUTRAL — maintain positions, watch for shifts.
  • 60-74DEFENSE — don't add, brace for volatility.
  • 75-100DEFENSE_HARD — trim, buy protection (long puts / collars).

Why This Is a Separate Skill

alphagbm-vix-status gives just a VIX tier. alphagbm-market-sentiment gives a sentiment dashboard. This skill is the one-call Marks-specific read: "given everything I know about sentiment + valuation, what's the posture?"

How to Use

Input: none (market-level, no ticker)

Output:

  • cycle_score: integer 0-100
  • posture: one of OFFENSE_HARD / OFFENSE / NEUTRAL / DEFENSE / DEFENSE_HARD
  • posture_zh, posture_en: natural-language prescription
  • components: per-signal {value, cycle_component} breakdown

Example Queries

  • where are we in the cycle right now → headline cycle number + posture
  • should I be playing offense or defense → posture directly answers
  • Howard Marks read on the market → same data, framed as Marks would
  • is this a buying cycle → cycle < 30 → yes; cycle > 60 → no
  • current sentiment across VIX and IV rank → components breakdown

Mock Data

Mock data in mock-data/marks-cycle/ — sample showing NEUTRAL position.

API Endpoint

GET /api/masters/marks-cycle

No body, no auth required.

Response shape:

{
  "success": true,
  "cycle_score": 47,
  "posture": "NEUTRAL",
  "posture_zh": "中性 — 维持既定仓位,观察情绪变化",
  "posture_en": "Neutral — maintain positions, watch sentiment",
  "components": {
    "vix": {"value": 22.5, "cycle_component": 48},
    "iv_rank": {"value": 55, "cycle_component": 45}
  },
  "timestamp": "2026-04-24T08:00:00"
}

Pricing: free — no auth, no credit deduction. 5-min cache.

Related Skills

Skill Relevance
alphagbm-vix-status Raw VIX tier without Marks's multi-signal blend
alphagbm-market-sentiment Fuller sentiment dashboard (VIX + P/C + F&G)
alphagbm-fear-score Per-ticker version of the same "where's the fear" idea

Powered by AlphaGBM — Real-data options & research intelligence. 10K+ users.