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.

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Repository: anthropics/knowledge-work-plugins
Last source activity: February 24, 2026 at 00:08
Detected SKILL.md language: English
Stars: 26,169
Forks: 3,059

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

# 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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enrich-lead

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