fundamental-manager

Automate cache-backed retrieval and refreshing of stock financial metrics with DuckDB storage.

Updated Jan 12, 2026
One-click install
npx skills add https://github.com/chinawrj/agent-skills-stock --skill fundamental-manager
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: fundamental-manager
Source: https://github.com/chinawrj/agent-skills-stock/tree/main/.github/skills/fundamental-manager
Command: npx skills add https://github.com/chinawrj/agent-skills-stock --skill fundamental-manager

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates the caching and retrieval of financial metrics for listed stocks, reducing manual data management and ensuring up-to-date figures in response to user questions.

Core Features & Use Cases

  • Intelligent cache strategy that automatically decides when to refresh data during disclosure windows.
  • Read from a DuckDB-backed cache or fetch fresh data online when needed.
  • Support for single and batch updates, recent-history views, and basic profitability filtering.
  • Python API and CLI-style commands for querying and updating fundamentals.

Quick Start

Request a smart fetch and cache update for a single stock by calling get_smart with its code, for example get_smart('300401').

Frequently Asked Questions about fundamental-manager

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

FAQPage Schema
How do I automate financial data caching for stock fundamentals?

Automate financial data caching by using an intelligent update policy that checks cache freshness and disclosure windows. The system reads from a DuckDB-backed cache and fetches fresh fundamentals online only when needed, reducing manual data management.

Can I batch update ROE and EPS metrics for multiple stock tickers?

Yes, you can batch update ROE, net profit, EPS, and other fundamentals across multiple tickers. The system supports batch updates and profitability filtering, storing the retrieved financial metrics in a DuckDB-backed cache for subsequent queries.

How does the intelligent update policy decide when to refresh cached stock data?

The intelligent update policy decides when to refresh cached stock data by evaluating disclosure windows, current cache freshness, and a 24-hour check interval. It automatically triggers a fresh online fetch for financial metrics only when these conditions indicate the cache is outdated.

Does DuckDB work well for storing and querying historical fundamentals?

DuckDB works well for storing and querying fundamentals by providing a local, high-performance cache for financial metrics. It supports on-demand queries of ROE and net profit, recent-history views, and profitability filtering across multiple tickers via a Python API.

What is the best way to query profitability metrics for a single listed stock?

The best way to query profitability metrics for a single listed stock is using the Python API. Call get_smart with the specific stock code to trigger an intelligent fetch and cache update, which returns up-to-date fundamentals while optimizing data retrieval.