Earnings Preview

OrganizationPopular

anthropics

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 to watch for [company] earnings", "pre-earnings", "earnings setup", or "preview Q[X] for [company]".

Overview

Publisher	anthropics
Repository	`financial-services`
Skill name	`earnings-preview`
Stars	38.4K
Forks	5.5K
Bundled files	Instructions only
License	Apache-2.0
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by anthropics on GitHub. Read the source before you install it.

Installation

Install the Earnings Preview AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/anthropics/financial-services/tree/main/plugins/agent-plugins/earnings-reviewer/skills/earnings-preview
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/anthropics/financial-services/tree/main/plugins/agent-plugins/earnings-reviewer/skills/earnings-preview

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/anthropics/financial-services.git /tmp/financial-services
mkdir -p .claude/skills
cp -r /tmp/financial-services/plugins/agent-plugins/earnings-reviewer/skills/earnings-preview .claude/skills/earnings-preview

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Earnings Preview in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Earnings Preview on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Earnings Preview is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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:

[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

What does the Earnings Preview AI skill do?

Why use Earnings Preview on TypingMind?

Because you install it once and use it with any model. Earnings Preview is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Earnings Preview in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/anthropics/financial-services/tree/main/plugins/agent-plugins/earnings-reviewer/skills/earnings-preview. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Earnings Preview?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Earnings Preview?

As many as you like. As long as a model supports skills, you can use Earnings Preview with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Earnings Preview AI skill free?

Yes. It is published on GitHub by anthropics under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Earnings Preview

Workflow

Step 1: Gather Context

Step 2: Key Metrics Framework

Step 3: Scenario Analysis

Step 4: Catalyst Checklist

Step 5: Output

Important Notes

Frequently asked questions

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