# Alpha Zoo

Browse and bench the bundled alpha zoos, prebuilt cross-sectional factor libraries...

- Repository: https://github.com/HKUDS/Vibe-Trading (37375 stars)
- Category: Engineering
- License: MIT
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add HKUDS/Vibe-Trading --skill alpha-zoo -g -a claude-code -y`
Codex: `npx skills add HKUDS/Vibe-Trading --skill alpha-zoo -g -a codex -y`
Cursor: `npx skills add HKUDS/Vibe-Trading --skill alpha-zoo -g -a cursor -y`
Gemini CLI: `npx skills add HKUDS/Vibe-Trading --skill alpha-zoo -g -a gemini-cli -y`

## Description

Browse and bench the bundled alpha zoos, prebuilt cross-sectional factor libraries (Kakushadze 101, GTJA 191, Qlib 158, Fama-French / Carhart). Use when the user asks "which alphas exist", wants metadata on a named alpha, or wants to run IC/IR on a whole zoo over a universe.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Alpha Zoo

## Purpose

When the user asks about prebuilt cross-sectional alphas, Kakushadze 101, GTJA 191, Qlib 158, Fama-French / Carhart, or wants to bench a whole zoo on an investable universe (CSI 300, S&P 500, BTC-USDT, ...), this skill orients you. The zoo is the curated library; the bench is the evaluator.

## Tools Available

| Tool | When to use |
|------|------|
| `alpha_zoo` | Browse the library. `action=list_alphas` to enumerate (filterable by zoo / theme / universe), `action=get_alpha` for one alpha's metadata, `action=health` for registry load status. |
| `alpha_bench` | Run IC / IR on one alpha or a whole zoo over a universe + period. Emits an HTML report. |
| `factor_analysis` | Ad-hoc factor evaluation from a user-supplied factor CSV + return CSV. Use this when the user has their own factor (not in the zoo). |

## Decision Tree

- "list all momentum alphas" → `alpha_zoo` with `action=list_alphas, theme=momentum`.
- "show me gtja191_alpha_001" → `alpha_zoo` with `action=get_alpha, alpha_id=gtja191_alpha_001`.
- "bench all of GTJA 191 on CSI 300 from 2020 to 2024" → `alpha_bench` with `zoo=gtja191, universe=csi300, period=2020-2024`.
- "is the registry healthy" → `alpha_zoo` with `action=health`, surfaces `loaded`, `failed`, and per-error reasons.
- User uploads `my_factor.csv` → `factor_analysis` (zoo tools are for prebuilt alphas only).

## Zoo Inventory

| Zoo | Description | Approx. count |
|------|------|------|
| `kakushadze101` | Formulaic alphas from Kakushadze's 2015 paper. Mix of momentum, reversal, volume, and microstructure. | ~101 |
| `gtja191` | Guotai Junan 191 alphas, A-share focused cross-sectional factors. | ~191 |
| `qlib158` | Microsoft Qlib's 158 alpha factors, features tuned for ML pipelines. | ~158 |
| `classical` | Fama-French 3/5-factor + Carhart momentum. | <10 |

Counts are nominal; check `alpha_zoo action=health` for the live count currently loaded.

## Constraints

The rest: https://github.com/HKUDS/Vibe-Trading/blob/HEAD/agent/src/skills/alpha-zoo/SKILL.md