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:

bash

pip install yfinance requests pandas

Core Capabilities#

1. Earnings Calendar Tracking — Automatically retrieve target company earnings release dates
2. Market Expectation Comparison — EPS/Revenue expectations vs. actual data
3. Earnings Interpretation — Key metric changes and management guidance summary

Command List#

CommandDescriptionUsagetrackTrack earnings release datespython scripts/earnings_tracker.py track <ticker>``previewEarnings preview analysispython scripts/earnings_tracker.py preview <ticker>``reviewEarnings interpretationpython scripts/earnings_tracker.py review <ticker> --quarter <Q1/Q2/Q3/Q4>

Usage Workflow#

Scenario 1: Track Earnings Date#

text

Track Apple's next earnings release date and market expectations

bash

python scripts/earnings_tracker.py track AAPL

Scenario 2: Earnings Preview Analysis#

text

Pre-earnings expectation analysis

bash

python scripts/earnings_tracker.py preview AAPL

Scenario 3: Earnings Review#

text

Interpret key data from the latest earnings report

bash

python scripts/earnings_tracker.py review AAPL --quarter Q1

Output Format#

All commands output a standard Markdown format report:

markdown

# 📊 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