Agent Skills
› AI4Finance-Foundation/FinRobot
› Earnings Preview
Earnings Preview
GitHub用于构建财报前分析，通过收集共识预期、关键指标框架及牛熊基三种情景分析，识别影响股价的核心催化剂，输出包含预估数据、情景推演和交易设置的单页预览报告。
Trigger Scenarios
earnings preview
what to watch for [company] earnings
pre-earnings
earnings setup
preview Q[X] for [company]
Install
npx skills add AI4Finance-Foundation/FinRobot --skill Earnings Preview -g -y
SKILL.md
Frontmatter
{
"id": "earnings-preview",
"name": "Earnings Preview",
"author": "anthropic",
"domain": "equity-research",
"version": "1.0.0",
"triggers": [
"earnings preview",
"what to watch for [company] earnings",
"pre-earnings",
"earnings setup",
"preview Q[X] for [company]"
],
"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 [com...",
"requires_data": [],
"requires_tools": [],
"requires_skills": [],
"compatible_models": []
}
Earnings Preview
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]".
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
Version History
- 2d059b2 Current 2026-09-28 18:33
