Earnings Preview Skill

Generates a pre-earnings briefing using Yahoo Finance data via yfinance. Pulls together upcoming earnings date, consensus estimates, historical accuracy, analyst sentiment, and key financial context — everything you need before an earnings call.

Important: Data is for research and educational purposes only. Not financial advice. yfinance is not affiliated with Yahoo, Inc.

Step 1: Ensure yfinance Is Available

Current environment status:

!`python3 -c "import yfinance; print('yfinance ' + yfinance.__version__ + ' installed')" 2>/dev/null || echo "YFINANCE_NOT_INSTALLED"`

If YFINANCE_NOT_INSTALLED, install it:

import subprocess, sys

subprocess.check_call([sys.executable, "-m", "pip", "install", "-q", "yfinance"])

If already installed, skip to the next step.

Step 2: Identify the Ticker and Gather All Data

Extract the ticker symbol from the user's request. If they mention a company name without a ticker, look it up. Then fetch all relevant data in one script to minimize API calls.

import yfinance as yf

import pandas as pd

from datetime import datetime

ticker = yf.Ticker("AAPL")  # replace with actual ticker

# --- Core data ---

info = ticker.info

calendar = ticker.calendar

# --- Estimates ---

earnings_est = ticker.earnings_estimate

revenue_est = ticker.revenue_estimate

# --- Historical track record ---

earnings_hist = ticker.earnings_history

# --- Analyst sentiment ---

price_targets = ticker.analyst_price_targets

recommendations = ticker.recommendations

# --- Recent financials for context ---

quarterly_income = ticker.quarterly_income_stmt

quarterly_cashflow = ticker.quarterly_cashflow

What to extract from each source

Data Source

Key Fields

Purpose

calendar

Earnings Date, Ex-Dividend Date

When earnings are and key dates

earnings_estimate

avg, low, high, numberOfAnalysts, yearAgoEps, growth (for 0q, +1q, 0y, +1y)

Consensus EPS expectations

revenue_estimate

avg, low, high, numberOfAnalysts, yearAgoRevenue, growth

Revenue expectations

earnings_history

epsEstimate, epsActual, epsDifference, surprisePercent

Beat/miss track record

analyst_price_targets

current, low, high, mean, median

Street price targets

recommendations

Buy/Hold/Sell counts

Sentiment distribution

quarterly_income_stmt

TotalRevenue, NetIncome, BasicEPS

Recent trajectory

Step 3: Build the Earnings Preview

Assemble the data into a structured briefing. The goal is to give the user everything they need in one glance.

Section 1: Earnings Date & Key Info

Report the upcoming earnings date from calendar. Include:

• Company name, ticker, sector, industry

• Upcoming earnings date (and whether it's before/after market)

• Current stock price and recent performance (1-week, 1-month)

• Market cap

Section 2: Consensus Estimates

Present the current quarter estimates from earnings_estimate and revenue_estimate:

Metric

Consensus

Low

High

Analysts

Year Ago

Growth

EPS

$1.42

$1.35

$1.50

28

$1.26

+12.7%

Revenue

$94.3B

$92.1B

$96.8B

25

$89.5B

+5.4%

If the estimate range is unusually wide (high/low spread > 20% of consensus), note that as a sign of high uncertainty.

Section 3: Historical Beat/Miss Track Record

From earnings_history, show the last 4 quarters:

Quarter

EPS Est

EPS Actual

Surprise

Beat/Miss

Q3 2024

$1.35

$1.40

+3.7%

Beat

Q2 2024

$1.30

$1.33

+2.3%

Beat

Q1 2024

$1.52

$1.53

+0.7%

Beat

Q4 2023

$2.10

$2.18

+3.8%

Beat

Summarize: "AAPL has beaten EPS estimates in 4 of the last 4 quarters by an average of 2.6%."

Section 4: Analyst Sentiment

From recommendations and analyst_price_targets:

• Current recommendation distribution (Strong Buy / Buy / Hold / Sell / Strong Sell)

• Price target range: low, mean, median, high vs. current price

• Implied upside/downside from mean target

Section 5: Key Metrics to Watch

Based on the quarterly financials, highlight 3-5 things the market will focus on:

• Revenue growth trend (accelerating or decelerating?)

• Margin trajectory (expanding or compressing?)

• Any notable line items that changed significantly quarter-over-quarter

• Segment breakdowns if available in the data

This section requires judgment — think about what matters for this specific company/sector.

Step 4: Respond to the User

Present the preview as a clean, structured briefing:

• Lead with the headline: "AAPL reports earnings on [date]. Here's what to expect."

• Show all 5 sections with clear headers and tables

• End with a brief summary: 2-3 sentences capturing the overall setup (bullish/bearish lean based on estimates, track record, and sentiment — frame as "the street expects" not personal recommendation)

Caveats to include

• Estimates can change up until the report date

• Historical beats don't guarantee future beats

• Yahoo Finance data may lag real-time consensus by a few hours

• This is not financial advice

Reference Files

• references/api_reference.md — Detailed yfinance API reference for earnings and estimate methods

Read the reference file when you need exact method signatures or edge case handling.