earnings-calendar
This skill retrieves upcoming earnings announcements for US stocks using the Financial Modeling Prep (FMP) API. Use this when the user requests earnings calendar data, wants to know which companies are reporting earnings in the upcoming week, or needs a weekly earnings review. The skill focuses on mid-cap and above companies (over $2B market cap) that have significant market impact, organizing the data by date and timing in a clean markdown table format. Supports multiple environments (CLI, Desktop, Web) with flexible API key management.
npx skills add BaggaT236/AI-Trading-Skills --skill earnings-calendar --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Earnings Calendar ## Overview This skill retrieves upcoming earnings announcements for US stocks using the Financial Modeling Prep (FMP) API. It focuses on companies with significant market capitalization (mid-cap and above, over $2B) that are likely to impact market movements. The skill generates organized markdown reports showing which companies are reporting earnings over the next week, grouped by date and timing (before market open, after market close, or time not announced). **Key Features**: - Uses FMP API for reliable, structured earnings data - Filters by market cap (>$2B) to focus on market-moving companies - Includes EPS and revenue estimates - Multi-environment support (CLI, Desktop, Web) - Flexible API key management - Organized by date, timing, and market cap ## Prerequisites ### FMP API Key This skill requires a Financial Modeling Prep API key. **Get Free API Key**: 1. Visit: https://site.financialmodelingprep.com/developer/docs 2. Sign up for free account 3. Receive API key immediately 4. Free tier: 250 API calls/day (sufficient for weekly earnings calendar) **API Key Setup by Environment**: **Claude Code (CLI)**: ```bash export FMP_API_KEY="your-api-key-here" ```
- Overview
- Prerequisites
- FMP API Key
- Core Workflow
- Step 1: Get Current Date and Calculate Target Week
- Step 2: Load FMP API Guide
- Step 3: API Key Detection and Configuration
- Step 4: Retrieve Earnings Data via FMP API
- Step 5: Process and Organize Data
- Step 6: Generate Markdown Report
- Step 7: Quality Assurance
- Step 8: Save and Deliver Report
- Fallback Mode (Step 8 Alternative): Manual Data Entry
- Use Cases and Examples
export FMP_API_KEY="your-api-key-here"
if [ ! -z "$FMP_API_KEY" ]; then
echo "✓ API key found in environment"
fi
python scripts/fetch_earnings_fmp.py 2025-11-03 2025-11-09
python scripts/fetch_earnings_fmp.py 2025-11-03 2025-11-09 "${API_KEY}"
python scripts/fetch_earnings_fmp.py 2025-11-03 2025-11-09 "${API_KEY}" > earnings_data.json
python scripts/generate_report.py earnings_data.json
python scripts/generate_report.py earnings_data.json earnings_calendar_2025-11-02.md
python scripts/fetch_earnings_fmp.py 2025-11-03 2025-11-09 > earnings_data.jsonWhat does the earnings-calendar skill do?
This skill retrieves upcoming earnings announcements for US stocks using the Financial Modeling Prep (FMP) API. Use this when the user requests earnings calendar data, wants to know which companies are reporting earnings in the upcoming week, or needs a weekly earnings review. The skill focuses on mid-cap and above companies (over $2B market cap) that have significant market impact, organizing the data by date and timing in a clean markdown table format. Supports multiple environments (CLI, Desktop, Web) with flexible API key management.
How do I install it?
Run `npx skills add BaggaT236/AI-Trading-Skills --skill earnings-calendar --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BaggaT236/AI-Trading-Skills, a repository with 118 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.