AGENT SKILL

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.

使用场景邮件与沟通
License 许可
Apache-2.0
最近更新
2026-11-14
Stars
★ 3.6w
Forks
3.9k

01 前言 Front Matter

name
enrich-lead
description
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.
argument-hint
[name, company, LinkedIn URL, or email]
user-invocable
true

03 SKILL.md 正文

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:

  1. Save to Apollo — Create this person as a contact via mcp__claude_ai_Apollo_MCP__apollo_contacts_create with run_dedupe: true
  2. Add to a sequence — Ask which sequence, then run the sequence-load flow
  3. 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
  4. Find similar people — Search for people with the same title/seniority at other companies

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