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Alphagbm Theme Research

CommunityPopular
AlphaGBM
alphagbm-theme-research

Group related tickers into investment themes — AI infra, HK dividend, EV supply chain, biotech catalysts — with theme-level AI summary and news keyword monitoring. Each theme is a named bag of tickers plus keywords the system watches for you. Use when: creating a themed basket, pulling up a theme's aggregated view, adding/removing tickers, monitoring news around a topic. Triggers on: "create an AI infra theme", "show my themes", "add MSFT to AI theme", "what's happening in HK dividend", "主题研究", "AI基建", "港股高息", "投资主题".

Overview

PublisherAlphaGBM
Repositoryskills
Skill namealphagbm-theme-research
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 Theme Research 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-theme-research .claude/skills/alphagbm-theme-research
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Alphagbm Theme Research 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 Theme Research 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 Theme Research 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 Theme Research

Group related tickers into named investment themes with an AI-generated summary and news keyword watchlist. Each theme is a lightweight basket you can track at the concept level.

When to use

  • User wants to organize tickers by theme (AI infra, HK dividend, EV supply chain, biotech…)
  • User asks to view a specific theme's holdings + latest summary
  • User wants to add or remove tickers from a theme
  • User wants the system to monitor news around a topic
  • User mentions "主题" / "theme" / "basket" / "篮子" / "板块"

Prerequisites

  • API Key: env ALPHAGBM_API_KEY (format agbm_xxxx…).
  • Base URL: default https://alphagbm.zeabur.app. Override via ALPHAGBM_BASE_URL.
  • Tier limits apply: Free tier is capped on themes — check_profile_limit mirrors the profile limit model. Check limits.max_themes via the dashboard endpoint.

API Endpoints

All endpoints require Authorization: Bearer $ALPHAGBM_API_KEY.

1. List themes

GET /api/research/themes

Response:

json
{
  "success": true,
  "themes": [
    {
      "id": 7,
      "theme_name": "AI Infrastructure",
      "description": "Picks & shovels for the AI capex cycle",
      "tickers": ["NVDA", "AVGO", "MSFT", "ORCL"],
      "news_keywords": ["AI capex", "data center", "hyperscaler"],
      "theme_summary": "Capex guidance up across 4 hyperscalers...",
      "last_updated_at": "2026-04-13T09:00:00Z"
    }
  ]
}

2. Get theme detail (aggregated)

GET /api/research/themes/<THEME_ID>

Returns the theme + aggregated data across its tickers (average price change, top movers, recent news matching keywords). 404 if not found or not owned.

3. Create theme

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

{
  "theme_name": "AI Infrastructure",
  "description": "Picks & shovels for AI capex",
  "tickers": ["NVDA", "AVGO", "MSFT"],
  "news_keywords": ["AI capex", "data center"]
}
ParameterTypeRequiredDescription
theme_namestringyesDisplay name, used to dedupe
descriptionstringnoShort blurb
tickersarray of stringnoInitial tickers; can be edited later
news_keywordsarray of stringnoPhrases monitored for news matches

4. Update theme (by id)

PUT /api/research/themes/<THEME_ID>
Content-Type: application/json

{"tickers": ["NVDA", "AVGO", "MSFT", "ORCL"], "news_keywords": [...]}

Partial update. Any of the fields from create are accepted.

5. Delete theme (by id)

DELETE /api/research/themes/<THEME_ID>

Hard-delete. Doesn't affect the underlying company profiles.

Response schema — theme

{
  id, theme_name, description,
  tickers,                  // array of ticker strings
  news_keywords,            // array of phrases for news matching
  theme_summary,            // AI-generated narrative (markdown)
  last_updated_at, created_at
}

Theme detail endpoint (GET /themes/<id>) additionally includes aggregated fields like top movers and recent matched news — the exact shape is service-side and stable for display, not for programmatic parsing.

Typical Workflow

1. User: "Create an AI infra theme with NVDA, AVGO, MSFT"
   → POST /api/research/themes
     {"theme_name": "AI Infrastructure", "tickers": ["NVDA","AVGO","MSFT"],
      "news_keywords": ["AI capex", "data center"]}
   → Confirm theme created; mention it'll start accumulating summary + news

2. User: "What themes do I have?"
   → GET /api/research/themes
   → Table: theme · ticker count · last updated · summary excerpt

3. User: "Add ORCL to my AI theme"
   → GET /api/research/themes (find id)
   → PUT /api/research/themes/<id> {"tickers": [... + "ORCL"]}

4. User: "What's happening in my HK dividend theme?"
   → GET /api/research/themes/<id>
   → Lead with theme_summary + aggregated movers + matched news

Output Formatting Tips

When presenting themes:

  1. List view — theme name · ticker count · "updated Xd ago" · 1-sentence summary
  2. Detail view — lead with theme_summary (AI narrative), then ticker grid with % change, then recent matched news
  3. Keyword hygiene — if the user creates a theme with no news_keywords, prompt: "Want me to watch for any news phrases? E.g., 'AI capex', 'hyperscaler'"
  4. Ticker overlap — when creating a new theme, check if tickers already exist in other themes; it's fine (tickers can be in multiple themes) but worth mentioning

Related Skills

  • alphagbm-company-profile — Themes reference profiles; creating a theme with untracked tickers still works but they won't have profile data
  • alphagbm-health-check — Flags orphan tickers that are in themes but no longer in any profile
  • alphagbm-compare — Side-by-side comparison for tickers within a theme

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

Frequently asked questions

What does the Alphagbm Theme Research AI skill do?

Group related tickers into investment themes — AI infra, HK dividend, EV supply chain, biotech catalysts — with theme-level AI summary and news keyword monitoring. Each theme is a named bag of tickers plus keywords the system watches for you. Use when: creating a themed basket, pulling up a theme's aggregated view, adding/removing tickers, monitoring news around a topic. Triggers on: "create an AI infra theme", "show my themes", "add MSFT to AI theme", "what's happening in HK dividend", "主题研究", "AI基建", "港股高息", "投资主题".

Why use Alphagbm Theme Research on TypingMind?

Because you install it once and use it with any model. Alphagbm Theme Research 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 Theme Research in TypingMind?

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

Which AI models can use Alphagbm Theme Research?

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 Theme Research?

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

Is the Alphagbm Theme Research 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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