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enrich-lead

by @anthropicsv
3.8(14)

Convert any identifier (email, LinkedIn, etc.) into a complete contact profile, assisting sales with precise lead acquisition.

lead-enrichmentsales-intelligencecrmlead-generationb2b-salesGitHub
Installation
npx skills add anthropics/knowledge-work-plugins --skill enrich-lead
compare_arrows

Before / After Comparison

1
Before

手动搜索LinkedIn和公司官网,信息分散不全,调研一个线索需要20分钟

After

输入任意标识符自动聚合完整档案,决策人背景一清二楚

description SKILL.md

enrich-lead

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

Weekly Installs215Repositoryanthropics/know…-pluginsGitHub Stars9.9KFirst SeenFeb 24, 2026Security AuditsGen Agent Trust HubPassSocketPassSnykPassInstalled oncodex202opencode202gemini-cli201cursor200github-copilot200amp200

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Installs405
Rating3.8 / 5.0
Version
Updated2026年3月20日
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Compatible Platforms

🔧Claude Code

Timeline

Created2026年3月20日
Last Updated2026年3月20日