Contains Shell Commands

This skill contains shell command directives (

!command

) that may execute system commands. Review carefully before installing.

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.