- name
- financial-report-tracker
- description
- Automatically track tech company financial reports and generate investment summaries. Supports retrieving earnings calendars, market expectation comparisons, key metric interpretation, and more.
Financial Report Tracker
Automatically track tech company financial reports and generate investment summaries. Suitable for investors tracking portfolio companies' earnings calendars and automatically summarizing earnings highlights and risks.
Use Cases
When users mention earnings reports, financial reports, EPS, revenue expectations, earnings interpretation, tracking a company's financials, and similar scenarios.
Prerequisites
Install Python dependencies before first use:
pip install yfinance requests pandasCore Capabilities
- Earnings Calendar Tracking — Automatically retrieve target company earnings release dates
- Market Expectation Comparison — EPS/Revenue expectations vs. actual data
- Earnings Interpretation — Key metric changes and management guidance summary
Command List
| Command | Description | Usage |
|---|---|---|
track | Track earnings release dates | python scripts/earnings_tracker.py track <ticker> |
preview | Earnings preview analysis | python scripts/earnings_tracker.py preview <ticker> |
review | Earnings interpretation | python scripts/earnings_tracker.py review <ticker> --quarter <Q1/Q2/Q3/Q4> |
Usage Workflow
Scenario 1: Track Earnings Date
Track Apple's next earnings release date and market expectationspython scripts/earnings_tracker.py track AAPLScenario 2: Earnings Preview Analysis
Pre-earnings expectation analysispython scripts/earnings_tracker.py preview AAPLScenario 3: Earnings Review
Interpret key data from the latest earnings reportpython scripts/earnings_tracker.py review AAPL --quarter Q1Output Format
All commands output a standard Markdown format report:
# 📊 Financial Report Tracker Report
**Generated on**: YYYY-MM-DD HH:MM
## Key Findings
1. [Key finding 1]
2. [Key finding 2]
3. [Key finding 3]
## Data Overview
| Metric | Value | Trend | Rating |
|--------|-------|-------|--------|
| Metric A | XXX | ↑ | ⭐⭐⭐⭐ |
| Metric B | YYY | → | ⭐⭐⭐ |
## Detailed Analysis
[Multi-dimensional analysis based on actual data]
## Actionable Recommendations
| Priority | Recommendation | Expected Outcome |
|----------|----------------|------------------|
| 🔴 High | [Specific recommendation] | [Quantified expectation] |
| 🟡 Medium | [Specific recommendation] | [Quantified expectation] |
| 🟢 Low | [Specific recommendation] | [Quantified expectation] |References
- yfinance Library — Earnings calendar and earnings data
- Financial Modeling Prep API — Financial report data
Notes
- All analysis is based on data retrieved by the script; data is not fabricated
- Missing data fields are marked "Data Unavailable" rather than guessed
- It is recommended to combine with human judgment; AI analysis is for reference only