Earnings Preview
OfficialFreePrepare for quarterly earnings with structured analysis.
Free · Opens the source repo
What Earnings Preview does
Earnings Preview is designed for analysts, investors, and finance professionals who need to prepare for company earnings reports. This skill provides a structured workflow to gather relevant data, analyze key metrics, and create actionable insights before earnings announcements. By focusing on consensus estimates, operational metrics, and scenario analysis, users can effectively position themselves for potential market movements based on earnings results.
The workflow begins by gathering essential context, including the company in question, the reporting quarter, and consensus estimates for revenue and earnings per share (EPS). Users are guided to review previous earnings calls for insights and to identify the timing of the earnings report. This foundational knowledge sets the stage for a detailed analysis of financial and operational metrics that are crucial for understanding the company's performance.
Next, users build a framework of key metrics specific to the company’s sector, such as annual recurring revenue for tech firms or same-store sales for retailers. Following this, the skill facilitates the creation of three distinct scenarios—bull, base, and bear—each outlining potential stock price implications based on different operational outcomes and management commentary. This scenario analysis is supported by historical context, enabling users to calibrate their expectations based on past performance.
Finally, the skill culminates in a one-page earnings preview that consolidates all findings, including a consensus estimates table, a ranked list of key metrics to watch, and a checklist of catalysts that could influence stock reactions. This structured approach not only aids in preparation but also enhances decision-making for trading strategies around earnings announcements.
When to use it
Use this skill when preparing for an upcoming earnings report to ensure you have a comprehensive understanding of the key metrics and potential market reactions.
When not to use it
This skill may not be suitable for casual investors or those unfamiliar with financial metrics, as it requires a certain level of financial knowledge to effectively utilize the insights generated.
What you can build with it
Pre-Earnings Analysis for Tech Company
Prepare a detailed earnings preview for a SaaS company, focusing on ARR and customer retention metrics.
Retail Earnings Setup
Analyze same-store sales and traffic metrics ahead of a major retail chain's earnings report.
Financial Sector Earnings Review
Create a catalyst checklist for a bank's earnings, focusing on loan growth and credit quality.
How to install Earnings Preview
View source1. Install with the skills CLI
npx skills add anthropics/financial-services/earnings-preview --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by anthropicsEarnings 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:
| Scenario | Revenue | EPS | Key Driver | Stock Reaction |
|---|---|---|---|---|
| Bull | ||||
| Base | ||||
| Bear |
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
Frequently asked questions about Earnings Preview
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