Enrich Lead

by anthropicsae1513ea94dcNo license27K starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated today

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.

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AI-generated overview

Enriches a lead from a name, company, LinkedIn URL, or email into a full contact card using Apollo.

What it does
Parses an identifier such as a name, company, LinkedIn URL, or email and resolves the person through Apollo people matching, falling back to a people search when the match fails. It then enriches the person's company for firmographic context and presents a formatted contact card with emails, phones, location, LinkedIn, and company revenue, funding, and headquarters. Finally it offers follow-up actions such as saving the contact to Apollo, adding them to a sequence, or finding colleagues or similar people.
When to use it
Use it when you have partial identifying information about a prospect and need a consolidated contact dossier. It suits sales or business development research where contact details and company context are needed before outreach.
Requirements
Requires access to the Apollo MCP tools (people match, mixed people search, organization enrich, contacts create) and network access to Apollo. Enrichment consumes Apollo credits, and the skill instructs warning the user before calling. Instructions only; no scripts are shipped.

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 [email protected]
  • /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

FieldDetail
Email (work)...
Email (personal)... (if revealed)
Phone (direct)...
Phone (mobile)...
Phone (corporate)...
LocationCity, State, Country
LinkedInURL
Company Domain...
Company RevenueRange
Company FundingTotal raised
Company HQLocation

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

Source and attribution

Source:anthropics/knowledge-work-pluginsinpartner-built/apollo/skills/enrich-leadat commitae1513e

License: No license

Content belongs to its original authors. SourceWeft indexes it from a public repository.

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