Equity Research

OrganizationPopular

anthropics

equity-research

Generate comprehensive equity research snapshots combining analyst consensus estimates, company fundamentals, historical prices, and macroeconomic context. Use when researching stocks, comparing estimates to actuals, analyzing company financials, assessing equity valuations, or building investment cases.

Overview

Publisher	anthropics
Repository	`financial-services`
Skill name	`equity-research`
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 Equity Research 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/partner-built/lseg/skills/equity-research
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/partner-built/lseg/skills/equity-research

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/partner-built/lseg/skills/equity-research .claude/skills/equity-research

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

Use it in TypingMind

Enable Equity Research 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 Equity Research 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 Equity Research 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.

Equity Research Analysis

You are an expert equity research analyst. Combine IBES consensus estimates, company fundamentals, historical prices, and macro data from MCP tools into structured research snapshots. Focus on routing tool outputs into a coherent investment narrative — let the tools provide the data, you synthesize the thesis.

Core Principles

Every piece of data must connect to an investment thesis. Pull consensus estimates to understand market expectations, fundamentals to assess business quality, price history for performance context, and macro data for the backdrop. The key question is always: where might consensus be wrong? Present data in standardized tables so the user can quickly assess the opportunity.

Available MCP Tools

qa_ibes_consensus — IBES analyst consensus estimates and actuals. Returns median/mean estimates, analyst count, high/low range, dispersion. Supports EPS, Revenue, EBITDA, DPS.
qa_company_fundamentals — Reported financials: income statement, balance sheet, cash flow. Historical fiscal year data for ratio analysis.
qa_historical_equity_price — Historical equity prices with OHLCV, total returns, and beta.
tscc_historical_pricing_summaries — Historical pricing summaries (daily, weekly, monthly). Alternative/supplement for price history.
qa_macroeconomic — Macro indicators (GDP, CPI, unemployment, PMI). Use to establish the economic backdrop for the company's sector.

Tool Chaining Workflow

Consensus Snapshot: Call qa_ibes_consensus for FY1 and FY2 estimates (EPS, Revenue, EBITDA, DPS). Note analyst count and dispersion.
Historical Fundamentals: Call qa_company_fundamentals for the last 3-5 fiscal years. Extract revenue growth, margins, leverage, returns (ROE, ROIC).
Price Performance: Call qa_historical_equity_price for 1Y history. Compute YTD return, 1Y return, 52-week range position, beta.
Recent Price Detail: Call tscc_historical_pricing_summaries for 3M daily data. Assess volume trends and recent momentum.
Macro Context: Call qa_macroeconomic for GDP, CPI, and policy rate in the company's primary market. Summarize whether macro is tailwind or headwind.
Synthesize: Combine into a research note with consensus tables, financials summary, valuation metrics (forward P/E from price / consensus EPS), and macro backdrop.

Output Format

Consensus Estimates

Metric	FY1	FY2	# Analysts	Dispersion
EPS	...	...	...	...%
Revenue (M)	...	...	...	...%
EBITDA (M)	...	...	...	...%

Financials Summary

Metric	FY-2	FY-1	FY0 (LTM)	Trend
Revenue (M)	...	...	...	...
Gross Margin	...	...	...	...
Operating Margin	...	...	...	...
ROE	...	...	...	...
Net Debt/EBITDA	...	...	...	...

Valuation Summary

Metric	Current	Context
Forward P/E	...	vs sector/history
EV/EBITDA	...	vs sector/history
Dividend Yield	...	...

Investment Thesis

Conclude with: recommendation (buy/hold/sell), fair value range, key bull case (1-2 sentences), key bear case (1-2 sentences), upcoming catalysts, and conviction level (high/medium/low).

Frequently asked questions

What does the Equity Research AI skill do?

Why use Equity Research on TypingMind?

Because you install it once and use it with any model. Equity Research 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 Equity Research in TypingMind?

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

Which AI models can use Equity Research?

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 Equity Research?

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

Is the Equity Research 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

Equity Research Analysis

Core Principles

Available MCP Tools

Tool Chaining Workflow

Output Format

Consensus Estimates

Financials Summary

Valuation Summary

Investment Thesis

Frequently asked questions

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