Earnings Preview Skill for Claude

Build pre-earnings analysis with estimate models, scenario frameworks, and key metrics to watch. Use before a company reports quarterly earnings to prepare positioning notes, set up bull/bear scenarios, and identify what will move the stock. Triggers on "earnings preview", "what to watch for [company] earnings", "pre-earnings", "earnings setup", or "preview Q[X] for [company]".

689 tokens

context cost

the whole folder, loaded on every use

files

instructions only

copies elsewhere

how many repositories repackaged it

33987

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/anthropics/financial-services --skill earnings-preview

The instruction itself

8 sections, as written by the author

Earnings Preview

Workflow

Step 1: Gather Context

Identify the company and reporting quarter
Pull consensus estimates via web search (revenue, EPS, key segment metrics)
Find the earnings date and time (pre-market vs. after-hours)
Review the company's prior quarter earnings call for any guidance or commentary

Step 2: Key Metrics Framework

Build a "what to watch" framework specific to the company:

Financial Metrics:

Revenue vs. consensus (total and by segment)
EPS vs. consensus
Margins (gross, operating, net) — expanding or contracting?
Free cash flow
Forward guidance vs. consensus

Operational Metrics (sector-specific):

Tech/SaaS: ARR, net retention, RPO, customer count
Retail: Same-store sales, traffic, basket size
Industrials: Backlog, book-to-bill, price vs. volume
Financials: NIM, credit quality, loan growth, fee income
Healthcare: Scripts, patient volumes, pipeline updates

Step 3: Scenario Analysis

Build 3 scenarios with stock price implications:

|----------|---------|-----|------------|----------------|

For each scenario:

What would need to happen operationally
What management commentary would signal this
Historical context — how has the stock moved on similar prints?

Step 4: Catalyst Checklist

Identify the 3-5 things that will determine the stock's reaction:

[Metric] vs. [consensus/whisper number] — why it matters
[Guidance item] — what the buy-side expects to hear
[Narrative shift] — any strategic changes, M&A, restructuring

Step 5: Output

One-page earnings preview with:

Company, quarter, earnings date
Consensus estimates table
Key metrics to watch (ranked by importance)
Bull/base/bear scenario table
Catalyst checklist
Trading setup: recent stock performance, implied move from options

Important Notes

Consensus estimates change — always note the source and date of estimates
"Whisper numbers" from buy-side surveys are often more relevant than published consensus
Historical earnings reactions help calibrate expectations (search for "[company] earnings reaction history")
Options-implied move tells you what the market expects — compare to your scenarios

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by himself65

> Generate a pre-earnings briefing for any stock using Yahoo Finance data. Use this skill whenever the user wants to prepare for an upcoming earnings report, understand what analysts expect, review a company's beat/miss track record, or get a quick overview before an earnings call. "MSFT reports next week", "earnings preview", "pre-earnings analysis", "what are analysts expecting for NVDA", "earnings estimates for", "will GOOGL beat earnings", "earnings beat/miss history", "upcoming earnings", "before earnings", "earnings setup", "consensus estimates", "earnings whisper", "EPS expectations", "what's the street expecting", "earnings season preview", any mention of preparing for or previewing an earnings report, or any request to understand expectations ahead of a company's earnings date. Always use this skill when the user mentions a ticker in context of upcoming earnings, even if they don't say "preview" explicitly.

3k tokens

How to use it

Copy the folder

Take anthropics/earnings-preview from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.