earnings-preview
The facts
Its description
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]".
The description the agent reads to decide when to use it.
When it starts
The agent picks this skill when someone wants to get ready for a company's upcoming quarterly earnings report before it happens — building a preview of consensus estimates, the metrics that matter, and bull/base/bear scenarios. It is aimed at pre-earnings positioning rather than analyzing results after the fact.
Things a person might say (the model's guesses)
- “Can you put together an earnings preview for NVDA before next week's print?”
- “What should I watch for in Apple's earnings this quarter?”
- “Help me set up bull and bear scenarios and a catalyst checklist for Tesla's Q3 earnings.”
A model's summary of when it is used.
Licence
Apache-2.0, from LICENSE
The terms its author shares it under, which let it be shown here.
The text
Earnings Preview
Raw lines 1 to 7Workflow
Raw lines 8 to 9Step 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
From anthropics/financial-services at 6056506, 2026-10-28. Skills read by DeepSeek V4.1 Flash on 2026-11-04. Summary and techniques by Claude Opus 5.5 on 2026-11-06.