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.