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.

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Step 1: Ensure yfinance Is Available

Current environment status:

!`python3 -c "exec('try:\n import yfinance\n print(\'yfinance \' + yfinance.__version__ + \' installed\')\nexcept Exception:\n print(\'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.

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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

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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.

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Step 4: Respond to the User

Present the preview as a clean, structured briefing:

1. Lead with the headline: "AAPL reports earnings on [date]. Here's what to expect."
2. Show all 5 sections with clear headers and tables
3. 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

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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.