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Earnings Preview

AnthropicOfficialPublished by Anthropic

  • Skill
  • Content generator
  • Business and productivity
  • Apache-2.0
  • No issues found
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From the author

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 by Anthropic

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The earnings-preview skill provides a structured framework for analyzing a company's upcoming quarterly financial results. It guides the user through gathering consensus estimates, identifying sector-specific operational metrics, and building bull, base, and bear scenarios. By synthesizing financial data with market expectations and historical context, the skill helps users prepare positioning notes and identify the primary catalysts likely to influence stock performance.

What it does

  • Aggregates consensus estimates for revenue, EPS, and key segment metrics.
  • Develops a customized framework of financial and operational metrics to monitor.
  • Constructs bull, base, and bear scenarios with associated stock price implications.
  • Creates a catalyst checklist to highlight critical factors driving market reaction.
  • Integrates historical earnings reaction data to calibrate expectations.
  • Summarizes findings into a concise one-page earnings preview report.

When to use it

  • Before a company reports its quarterly earnings.
  • When preparing investment positioning notes or research reports.
  • To establish a structured framework for evaluating potential stock price movements.
  • When assessing market expectations versus internal scenario analysis.

Advantages

  • Standardizes the preparation process for earnings events.
  • Forces consideration of both financial and operational drivers.
  • Helps quantify potential stock reactions through scenario modeling.
  • Provides a clear, actionable summary of critical catalysts.

Usage examples

“earnings preview for Apple Q3”
The agent generates a report detailing Apple's consensus revenue and EPS, key metrics like services revenue and iPhone sales, a scenario table, and a list of catalysts to watch.
“what to watch for Tesla earnings”
The agent provides a structured analysis focusing on automotive margins, delivery numbers, and forward guidance, along with a bull/bear scenario breakdown.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/anthropics/earnings-preview/download

  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip earnings-preview.zip -d .agents/skills

Documentation by Anthropic

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:

ScenarioRevenueEPSKey DriverStock 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

Files

ATTRIBUTION.md

Attribution

This folder is an unmodified copy of the Agent Skill "earnings-preview", distributed by AutoGineer (https://autogineer.com/agent-skills).

The skill's own files are unmodified copies. AutoGineer is not affiliated with or endorsed by the author or the publisher.

Files added by AutoGineer

  • ATTRIBUTION.md: this file, written by AutoGineer

  • LICENSE: copied from LICENSE

Requirements and compatibility

Written for: Claude Code, Claude apps

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

No issues found by our static scan· No issues found

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by
Anthropic
Publisher
Anthropic (Official)
Source
anthropics/financial-services · plugins/agent-plugins/earnings-reviewer/skills/earnings-preview · commit 6056506
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced
Also distributed in
anthropics/financial-services

AutoGineer is not affiliated with or endorsed by Anthropic or Anthropic.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download earnings-preview.zip