Enrich Lead

OrganizationPopular

anthropics

enrich-lead

Instant lead enrichment. Drop a name, company, LinkedIn URL, or email and get the full contact card with email, phone, title, company intel, and next actions.

Overview

Publisher	anthropics
Repository	`knowledge-work-plugins`
Skill name	`enrich-lead`
Stars	25.9K
Forks	3K
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 Enrich Lead 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/knowledge-work-plugins/tree/main/partner-built/apollo/skills/enrich-lead
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/knowledge-work-plugins/tree/main/partner-built/apollo/skills/enrich-lead

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/knowledge-work-plugins.git /tmp/knowledge-work-plugins
mkdir -p .claude/skills
cp -r /tmp/knowledge-work-plugins/partner-built/apollo/skills/enrich-lead .claude/skills/enrich-lead

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

Use it in TypingMind

Enable Enrich Lead 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 Enrich Lead 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 Enrich Lead 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.

Enrich Lead

Turn any identifier into a full contact dossier. The user provides identifying info via "$ARGUMENTS".

Examples

/apollo:enrich-lead Tim Zheng at Apollo
/apollo:enrich-lead https://www.linkedin.com/in/timzheng
/apollo:enrich-lead sarah@stripe.com
/apollo:enrich-lead Jane Smith, VP Engineering, Notion
/apollo:enrich-lead CEO of Figma

Step 1 — Parse Input

From "$ARGUMENTS", extract every identifier available:

First name, last name
Company name or domain
LinkedIn URL
Email address
Job title (use as a matching hint)

If the input is ambiguous (e.g. just "CEO of Figma"), first use mcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_search with relevant title and domain filters to identify the person, then proceed to enrichment.

Step 2 — Enrich the Person

Credit warning: Tell the user enrichment consumes 1 Apollo credit before calling.

Use mcp__claude_ai_Apollo_MCP__apollo_people_match with all available identifiers:

first_name, last_name if name is known
domain or organization_name if company is known
linkedin_url if LinkedIn is provided
email if email is provided
Set reveal_personal_emails to true

If the match fails, try mcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_search with looser filters and present the top 3 candidates. Ask the user to pick one, then re-enrich.

Step 3 — Enrich Their Company

Use mcp__claude_ai_Apollo_MCP__apollo_organizations_enrich with the person's company domain to pull firmographic context.

Step 4 — Present the Contact Card

Format the output exactly like this:

[Full Name] | [Title] [Company Name] · [Industry] · [Employee Count] employees

Field	Detail
Email (work)	...
Email (personal)	... (if revealed)
Phone (direct)	...
Phone (mobile)	...
Phone (corporate)	...
Location	City, State, Country
LinkedIn	URL
Company Domain	...
Company Revenue	Range
Company Funding	Total raised
Company HQ	Location

Step 5 — Offer Next Actions

Ask the user which action to take:

Save to Apollo — Create this person as a contact via mcp__claude_ai_Apollo_MCP__apollo_contacts_create with run_dedupe: true
Add to a sequence — Ask which sequence, then run the sequence-load flow
Find colleagues — Search for more people at the same company using mcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_search with q_organization_domains_list set to this company
Find similar people — Search for people with the same title/seniority at other companies

Frequently asked questions

What does the Enrich Lead AI skill do?

Instant lead enrichment. Drop a name, company, LinkedIn URL, or email and get the full contact card with email, phone, title, company intel, and next actions.

Why use Enrich Lead on TypingMind?

Because you install it once and use it with any model. Enrich Lead 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 Enrich Lead in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/anthropics/knowledge-work-plugins/tree/main/partner-built/apollo/skills/enrich-lead. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Enrich Lead?

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 Enrich Lead?

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

Is the Enrich Lead 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

Enrich Lead

Examples

Step 1 — Parse Input

Step 2 — Enrich the Person

Step 3 — Enrich Their Company

Step 4 — Present the Contact Card

Step 5 — Offer Next Actions

Frequently asked questions

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