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Enrich leads from basic identifiers into full contact details and next steps.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "enrich-lead" skill from askskill: 1. Download https://raw.githubusercontent.com/anthropics/knowledge-work-plugins/main/partner-built/apollo/skills/enrich-lead/SKILL.md 2. Save it as ~/.claude/skills/enrich-lead/SKILL.md 3. Reload skills and tell me it's ready
Please enrich this contact from the LinkedIn URL and return the name, title, company, email, phone, company overview, and recommended next outreach actions: https://www.linkedin.com/in/example
A complete contact card with usable contact details, company intelligence, and recommended follow-up actions.
Here is a prospect email: [email protected]. Please enrich her profile with title, company, phone, company size, industry details, and suggest the best first outreach approach.
An enriched prospect profile from the email, helping sales or marketing teams prioritize quickly.
Using the name “Alex Chen” and company “Acme Robotics,” enrich this person’s work details and contact information, then summarize three company insights worth mentioning in an outreach email.
Contact details, work information, and practical outreach angles ready to use in messaging.
Turn any identifier into a full contact dossier. The user provides identifying info via "$ARGUMENTS".
/apollo:enrich-lead Tim Zheng at Apollo/apollo:enrich-lead https://www.linkedin.com/in/timzheng/apollo:enrich-lead [email protected]/apollo:enrich-lead Jane Smith, VP Engineering, Notion/apollo:enrich-lead CEO of FigmaFrom "$ARGUMENTS", extract every identifier available:
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.
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 knowndomain or organization_name if company is knownlinkedin_url if LinkedIn is providedemail if email is providedreveal_personal_emails to trueIf 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.
Use mcp__claude_ai_Apollo_MCP__apollo_organizations_enrich with the person's company domain to pull firmographic context.
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 |
| URL | |
| Company Domain | ... |
| Company Revenue | Range |
| Company Funding | Total raised |
| Company HQ | Location |
Ask the user which action to take:
mcp__claude_ai_Apollo_MCP__apollo_contacts_create with run_dedupe: truemcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_search with q_organization_domains_list set to this companyEmbed Zoom Virtual Agent chat on web with secure controls and context updates.
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