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.