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/earnings-preview

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

From plugin
financial-services
34k118 skills10 agents56 commands2 MCP
Install
$ npx -y skills add anthropics/financial-services --skill earnings-preview --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/earnings-preview

Context preview

The summary Claude sees to decide when to auto-load this skill.

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

SKILL.md

earnings-preview.SKILL.md
name: 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]".

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:

| 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:

1. [Metric] vs. [consensus/whisper number] — why it matters 2. [Guidance item] — what the buy-side expects to hear 3. [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
Read more
Ships withfinancial-services

Reference agents, skills, and data connectors for the financial-services workflows we see most — investment banking, equity research, private equity, and wealth management.

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Other skills on financial-services.