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Alphagbm Macro View

CommunityPopular
AlphaGBM
alphagbm-macro-view

Track the macro variables that actually move your portfolio — VIX, US10Y, DXY, gold, oil, etc. — with auto-computed impact on user's holdings. Each tracked indicator returns current value, change, and AI-generated impact analysis linked to the user's profiles. Use when: adding a macro indicator, pulling current macro dashboard, asking how VIX affects the portfolio. Triggers on: "track VIX", "current 10-year yield", "how's the dollar doing", "add gold to my macro watch", "remove US10Y", "宏观指标", "美债利率", "美元指数", "VIX恐慌指数".

Overview

PublisherAlphaGBM
Repositoryskills
Skill namealphagbm-macro-view
Stars
2.7K
Forks
290
Bundled files
Instructions only
LicenseMIT
Links
  • 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 Macro View AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. 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.
2

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-macro-view .claude/skills/alphagbm-macro-view
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Alphagbm Macro View 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 Macro View 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 Macro View 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 Macro View

Track key macro indicators — VIX, US10Y, DXY, gold, oil, BTC, etc. — in the user's knowledge base. Each indicator comes with auto-computed impact analysis linked to the user's actual holdings.

When to use

  • User wants to start tracking a macro variable (VIX, yields, USD, gold…)
  • User asks for current macro dashboard / snapshot
  • User asks how a macro change affects their portfolio
  • User wants to stop tracking an indicator
  • User mentions "宏观" / "VIX" / "美债" / "美元" / "macro" / "yield"

Prerequisites

  • API Key: env ALPHAGBM_API_KEY (format agbm_xxxx…).
  • Base URL: default https://alphagbm.zeabur.app. Override via ALPHAGBM_BASE_URL.
  • No profile requirement — macro tracking is independent of the company profile list.

API Endpoints

All endpoints require Authorization: Bearer $ALPHAGBM_API_KEY.

1. List tracked indicators (also returns supported catalog)

GET /api/research/macro

Response:

json
{
  "success": true,
  "indicators": [
    {
      "indicator_key": "VIX",
      "display_name": "CBOE Volatility Index",
      "current_value": 18.2,
      "previous_value": 16.8,
      "change_pct": 8.3,
      "impact_analysis": "Rising VIX — elevated uncertainty. Your NVDA & TSLA positions are high-beta; consider…",
      "last_updated_at": "2026-04-13T10:15:00Z"
    }
  ],
  "supported": {
    "VIX":    {"name": "CBOE Volatility Index",   "category": "volatility"},
    "US10Y":  {"name": "US 10-Year Treasury",     "category": "yields"},
    "DXY":    {"name": "US Dollar Index",         "category": "currency"},
    "GOLD":   {"name": "Gold Spot",               "category": "commodity"},
    ...
  }
}

The supported field is the catalog of valid indicator_key values. Use it to present options when the user asks "what can I track".

2. Add indicator

POST /api/research/macro
Content-Type: application/json

{"indicator_key": "VIX"}
ParameterTypeRequiredDescription
indicator_keystringyesMust be in the supported catalog

400 response for unsupported keys:

json
{
  "success": false,
  "error": "Unsupported indicator. Supported: ['VIX', 'US10Y', 'DXY', ...]"
}

3. Remove indicator

DELETE /api/research/macro/<INDICATOR_KEY>

Uses the key (VIX, not an id). 404 if not tracked.

Response schema — indicator

{
  id, indicator_key,
  display_name,              // human-readable name
  current_value,             // most recent reading
  previous_value,            // for change_pct computation
  change_pct,                // % change
  impact_analysis,           // AI-generated, references user's holdings
  last_updated_at
}

Common indicator keys

KeyMeaningWhy it matters
VIXCBOE Volatility IndexRisk sentiment, option pricing
US10YUS 10-Year Treasury YieldDiscount rate, bond-equity rotation
US2YUS 2-Year YieldRate-hike expectations
DXYUS Dollar IndexEM / commodity / multinational earnings
GOLDGold spotHedge, real-yield inverse
OILWTI crudeInflation / energy sector
BTCBitcoinRisk appetite, crypto-adjacent stocks
HKDHKD liquidityHK market liquidity signal

Always call GET /api/research/macro first to fetch the live supported catalog — keys may be added/retired.

Typical Workflow

1. User: "Track VIX and the 10-year yield"
   → POST /api/research/macro {"indicator_key": "VIX"}
   → POST /api/research/macro {"indicator_key": "US10Y"}
   → Confirm both added with their current values

2. User: "What's the macro picture?"
   → GET /api/research/macro
   → Present each indicator: value, change, impact on their holdings

3. User: "Stop tracking DXY"
   → DELETE /api/research/macro/DXY

4. User: "Is high VIX hurting my positions?"
   → GET /api/research/macro → read VIX's impact_analysis field
   → The impact_analysis already references the user's specific holdings

Output Formatting Tips

When presenting macro indicators:

  1. Table-first for multi-indicator views: key · value · change% · one-line impact
  2. Highlight change direction with arrow/color (↑ red for VIX/yields up, ↓ green etc.)
  3. Lead with impact_analysis when user asks "how does X affect my portfolio" — it's pre-computed with their holdings in mind
  4. Stale data — if last_updated_at > 1d old, note "data may be stale, refresh coming"
  5. When user asks "what can I track", show the supported catalog grouped by category

Related Skills

  • alphagbm-company-profile — Macro impact analysis references the user's profiles
  • alphagbm-market-sentiment — Broader cross-asset sentiment read
  • alphagbm-iv-rank — Options-specific volatility context

Powered by AlphaGBM — Real-data options & research intelligence for traders and AI agents. 10K+ users.

Frequently asked questions

What does the Alphagbm Macro View AI skill do?

Track the macro variables that actually move your portfolio — VIX, US10Y, DXY, gold, oil, etc. — with auto-computed impact on user's holdings. Each tracked indicator returns current value, change, and AI-generated impact analysis linked to the user's profiles. Use when: adding a macro indicator, pulling current macro dashboard, asking how VIX affects the portfolio. Triggers on: "track VIX", "current 10-year yield", "how's the dollar doing", "add gold to my macro watch", "remove US10Y", "宏观指标", "美债利率", "美元指数", "VIX恐慌指数".

Why use Alphagbm Macro View on TypingMind?

Because you install it once and use it with any model. Alphagbm Macro View 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 Macro View in TypingMind?

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

Which AI models can use Alphagbm Macro View?

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 Macro View?

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

Is the Alphagbm Macro View 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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