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earnings-calendar

Fetch US earnings announcements from the FMP API and output JSON.

2.6k|600|Updated Oct 19, 2025
Search Tags:#API#Python#calendar#data-processing#earnings#stock-market#FMP
One-click install
npx skills add https://github.com/tradermonty/claude-trading-skills --skill earnings-calendar
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: earnings-calendar
Source: https://github.com/tradermonty/claude-trading-skills/tree/main/skills/earnings-calendar
Command: npx skills add https://github.com/tradermonty/claude-trading-skills --skill earnings-calendar

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This skill helps traders and investors quickly identify US earnings announcements for mid-cap+ companies (>$2B market cap) that are likely to move markets, and presents the data in a clean, report-ready format.

Core Features & Use Cases

  • Earnings calendar retrieval: Connects to Financial Modeling Prep (FMP) API to fetch upcoming earnings dates.
  • Market-cap filtering: Focuses on mid-cap+ names to prioritize market-moving events.
  • Multi-environment output: Outputs JSON for programmatic consumption and markdown render for reports.
  • Usage example: If you want to see which U.S. stocks are reporting earnings next week, this skill fetches data, enriches it with basic company metadata, and sorts by date and market cap.

Quick Start

Run the fetcher for the current target week with your API key and generate a markdown earnings calendar:

  1. Set your API key (env var or prompt)
  2. Fetch earnings: python scripts/fetch_earnings_fmp.py 2025-11-03 2025-11-09
  3. Generate a report: python scripts/generate_report.py earnings_data.json earnings_calendar.md

Frequently Asked Questions about earnings-calendar

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

FAQPage Schema
How do I fetch upcoming US stock earnings announcements using Python?▼

To fetch upcoming US stock earnings announcements, this Skill uses the requests library to connect to the Financial Modeling Prep API, retrieves data for your target dates, and outputs structured JSON. It requires your FMP API key to authenticate the HTTP requests.

Can I filter earnings calendar data to only include mid-cap and large-cap stocks?▼

Yes, you can filter earnings calendar data to focus on mid-cap and above companies with market caps exceeding $2 billion. This filtering prioritizes market-moving events, ensuring the output JSON and markdown reports highlight the most impactful upcoming earnings announcements.

What is the best way to generate a weekly earnings report from API data?▼

The best way to generate a weekly earnings report is to run the fetch script for specific date ranges, enrich the data with company profile fields, and then pass the structured JSON to a markdown generation script. This produces a clean, report-ready markdown file for weekly analysis.

Do I need an FMP API key to retrieve earnings calendar data in Python?▼

Yes, you need an FMP API key to retrieve earnings calendar data. The script handles the API key via environment variable or prompt input to authenticate requests against the Financial Modeling Prep endpoint and fetch the upcoming earnings dates successfully.

How does market cap filtering work for stock market earnings data?▼

Market cap filtering for stock market earnings data works by targeting companies above a $2 billion valuation. This approach removes small-cap noise from the earnings calendar, allowing traders to concentrate on market-moving announcements grouped by date and timing for weekly reporting.

Can I export FMP earnings data to JSON for downstream analysis?▼

Yes, you can export FMP earnings data to JSON for downstream analysis. The Python script fetches the earnings announcements, enriches them with basic profile fields, and outputs a structured JSON file ready for programmatic consumption or markdown report generation.

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