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This collection provides a suite of financial intelligence tools designed for quantitative traders and AI agents. It focuses on the precise calculation and interpretation of options Greeks and earnings-related volatility panels.
By integrating these specialized skills into development environments like Claude Code or Cursor, users can automate the analysis of complex derivatives metrics and structure financial data for more accurate decision-making.
WHO IT'S FOR
Quantitative traders
analyzing options Greeks and IV rank
AI agent builders
integrating financial intelligence into AI agents
Portfolio managers
performing hedge analysis and backtesting
Equity research analysts
conducting company profiles and investment thesis analysis
Compatible AgentsThe repository documents support for these agents. The skills may also work with other agents that can load SKILL.md files, but they may need some setup or small changes.
Follow the documented setup, then try a first task.
I’m using
Claude Code project clone
Installs: Complete AlphaGBM Skills bundle (29 open skills); skillPaths is a bounded selection of positively supported paths, not the complete bundle inventory. · Claude Code
Before you start
For live alphagbm-vix-status requests, an ALPHAGBM_API_KEY is required and must be sent as Authorization: Bearer $ALPHAGBM_API_KEY.
For live alphagbm-marks-cycle requests, an API key or supported user token is required.
No API key is needed when explicitly using supported bundled samples.
Run from: Project root
In a terminal, from the project root, clone the complete repository into the documented Claude Code skills directory.
Installs: Complete AlphaGBM Skills bundle (29 open skills), added as a Git submodule; skillPaths is a bounded selection of positively supported paths, not the complete bundle inventory. · Claude Code
Before you start
For live alphagbm-vix-status requests, an ALPHAGBM_API_KEY is required and must be sent as Authorization: Bearer $ALPHAGBM_API_KEY.
For live alphagbm-marks-cycle requests, an API key or supported user token is required.
No API key is needed when explicitly using supported bundled samples.
Run from: Project root
In a terminal, from the project root, add the complete repository at the documented Claude Code skills path as a submodule.
Installs: Complete AlphaGBM Skills bundle (29 open skills); skillPaths is a bounded selection of positively supported paths, not the complete bundle inventory. · Cursor
Before you start
For live alphagbm-vix-status requests, an ALPHAGBM_API_KEY is required and must be sent as Authorization: Bearer $ALPHAGBM_API_KEY.
For live alphagbm-marks-cycle requests, an API key or supported user token is required.
No API key is needed when explicitly using supported bundled samples.
In a terminal, clone the complete repository into the documented Cursor skills directory.
Use the alphagbm-compare skill and the bundled mock data to compare AAPL vs MSFT. Show the side-by-side dimensions, identify each category winner, and briefly explain the key differentiator behind the overall ranking.
Use the alphagbm-market-sentiment skill with the bundled sentiment-dashboard sample. Give me a concise dashboard covering VIX, put/call ratio, Fear & Greed, breadth, sector rotation, and the resulting risk-on, risk-off, or neutral regime classification.
Use the alphagbm-research-insights skill to list up to five latest published US-market insights in English, open the newest result using its returned slug, and provide a short neutral summary with its publication time, main evidence or assumptions, uncertainties, and original article URL. If there are no matching results, say so without substituting another market.