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Alpha Zoo Explorer

Browse prebuilt stock factor libraries and benchmark them with IC/IR stats

Source Download skill
Repository
HKUDS/Vibe-Trading
Stars
37,433
Licence
MIT
Files
1 file

What it does

This skill teaches an AI agent to navigate a bundled library of prebuilt investment 'alpha' factors (formulas that try to predict which assets will outperform), such as Kakushadze 101, GTJA 191, Qlib 158 and Fama-French/Carhart. The agent can list alphas by theme, look up one alpha's details, check the registry's health, and run an evaluation (IC/IR statistics) over a whole library on a market universe like CSI 300 or S&P 500, producing an HTML report. It also routes users with their own factor files to a separate factor analysis tool.

Great for

  • Quantitative researchers who want to compare many published factor formulas quickly
  • Students learning cross-sectional factor investing who want to browse named alphas
  • Analysts checking whether a known factor library still shows predictive power on a chosen market and period

Skip it if

  • Making live trading decisions: the skill only produces historical evaluation statistics and the source doesn't claim predictive reliability; past IC/IR results do not guarantee future returns
  • Users expecting per-stock factor values or raw data exports: the skill deliberately withholds underlying per-stock, per-date values and shows only aggregate stats and top-N summaries
  • Markets whose data loaders are not finished: the SKILL.md notes some universes return 'not yet implemented' errors

Try asking

  • “List all momentum alphas in the bundled zoos”
  • “Show me the details of gtja191_alpha_001”
  • “Bench all of GTJA 191 on CSI 300 from 2020 to 2024”
  • “Check whether the alpha registry is loaded and healthy”
Step-by-step guide: how to use Alpha Zoo ExplorerInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 1 original files, the MIT licence and an attribution note.

    alpha-zoo.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip alpha-zoo.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip alpha-zoo.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Use exact metadata values for filters such as theme and universe (for example equity_cn rather than cn or china), since mismatches return nothing
  • Run the health check first to see how many alphas are actually loaded, because counts in the docs are nominal
  • Pass either a single alpha_id or a zoo to alpha_bench, not both, and refer to report locations by their shorthand path

What's inside

  • SKILL.md

Redistributed unmodified from HKUDS/Vibe-Trading under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.