alpha-library

Manage factor metadata with CRUD operations in a SQLite-backed registry.

81|13|Updated Apr 3, 2026
One-click install
npx skills add https://github.com/VernonOY/alpha-skills --skill alpha-library
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: alpha-library
Source: https://github.com/VernonOY/alpha-skills/tree/main/skills/alpha-library
Command: npx skills add https://github.com/VernonOY/alpha-skills --skill alpha-library

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The Factor Library helps data scientists and quants manage their registered factors in a local SQLite database, enabling easy registration, listing, searching, and retirement of factors with persistent storage.

Core Features & Use Cases

  • Register factors with name, expression, category, market, and description, and store evaluation metadata (IC, ICIR, best holding period, and quality).
  • List, search, detail, and retire factors in a lightweight, self-contained registry for multi-market analysis.

Quick Start

Register a factor with its name and expression, then list or search to manage your factor registry.

Frequently Asked Questions about alpha-library

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I manage a local registry of quantitative factors with SQLite?

You can manage a local factor library using a SQLite-backed Python API that supports registering, listing, searching, and retiring factors with persistent local storage. It stores factor metadata like ic_mean and icir for multi-market analysis.

What metadata can I store when registering factors in a local database?

When registering factors, you can store name, expression, category, market, description, and evaluation metrics including ic_mean, icir, best_holding_period, and quality. This metadata enables effective factor search and multi-market analysis.

How do I persistently register and retire factors across multi-market contexts?

You can persistently register and retire factors across multi-market contexts using a lightweight Python API with CRUD operations. The SQLite storage ensures your factor registry remains safely persisted locally.

Does this factor library require external database dependencies?

No, the factor library relies on a self-contained SQLite database and requires no external dependencies. It provides a lightweight Python API for all CRUD operations directly on your local machine.

How do I search and list factors in a SQLite registry?

You search and list factors in a SQLite registry using the provided Python API functions. The API allows you to retrieve factor details, update status, and list registered factors based on your multi-market search criteria.