Alphagbm Marks Cycle

CommunityPopular

AlphaGBM

alphagbm-marks-cycle

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. Authenticated signal, no analysis-credit deduction, 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"

Overview

Publisher	AlphaGBM
Repository	`skills`
Skill name	`alphagbm-marks-cycle`
Stars	2.7K
Forks	290
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by AlphaGBM on GitHub. Read the source before you install it.

Installation

Install the Alphagbm Marks Cycle AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/AlphaGBM/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/alphagbm-marks-cycle .claude/skills/alphagbm-marks-cycle

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Alphagbm Marks Cycle in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Alphagbm Marks Cycle on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Alphagbm Marks Cycle is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

0-24 → OFFENSE_HARD — extreme fear is opportunity. Buy aggressively.
25-39 → OFFENSE — add, sell vol (short premium).
40-59 → NEUTRAL — maintain positions, watch for shifts.
60-74 → DEFENSE — don't add, brace for volatility.
75-100 → DEFENSE_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. Requires an authenticated request (API key or supported user token).

Response shape:

json
{
  "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: no analysis-credit deduction; authentication is still required. 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.

Frequently asked questions

What does the Alphagbm Marks Cycle AI skill do?

Why use Alphagbm Marks Cycle on TypingMind?

Because you install it once and use it with any model. Alphagbm Marks Cycle is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Alphagbm Marks Cycle in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AlphaGBM/skills/tree/main/skills/alphagbm-marks-cycle. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Alphagbm Marks Cycle?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Alphagbm Marks Cycle?

As many as you like. As long as a model supports skills, you can use Alphagbm Marks Cycle with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Alphagbm Marks Cycle AI skill free?

Yes. It is published on GitHub by AlphaGBM under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

AlphaGBM Howard Marks Cycle

The Cycle Score

Posture Bands

Why This Is a Separate Skill

How to Use

Example Queries

Mock Data

API Endpoint

Related Skills

Frequently asked questions

Related AI Skills

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