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Describe your ideal customer and get ranked enriched decision-maker leads.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "prospect" skill from askskill: 1. Download https://raw.githubusercontent.com/anthropics/knowledge-work-plugins/main/partner-built/apollo/skills/prospect/SKILL.md 2. Save it as ~/.claude/skills/prospect/SKILL.md 3. Reload skills and tell me it's ready
Find B2B SaaS companies in North America with 50-200 employees that have sales teams and may need customer support automation tools. Return a ranked list of decision-makers with company name, contact, title, email, phone number, and why they match.
A ranked prospect table with company details, decision-maker contacts, and match rationale.
My ideal customers are ecommerce brands selling through their own sites, with estimated revenue between $5M and $30M, focused on beauty or wellness, and actively running Facebook ads. Give me founders or marketing leaders with contact details.
A list of matching brands and key contacts with emails, phone numbers, and fit notes.
Generate a sales development list for mid-sized manufacturing companies in London, UK. Prioritize firms with digital transformation needs and list operations or IT leaders with contact details.
A regional lead list ready for outbound calls or email outreach.
Go from an ICP description to a ranked, enriched lead list in one shot. The user describes their ideal customer via "$ARGUMENTS".
/apollo:prospect VP of Engineering at Series B+ SaaS companies in the US, 200-1000 employees/apollo:prospect heads of marketing at e-commerce companies in Europe/apollo:prospect CTOs at fintech startups, 50-500 employees, New York/apollo:prospect procurement managers at manufacturing companies with 1000+ employees/apollo:prospect SDR leaders at companies using Salesforce and OutreachExtract structured filters from the natural language description in "$ARGUMENTS":
Company filters:
q_organization_keyword_tagsorganization_num_employees_rangesorganization_locationsq_organization_domains_listPerson filters:
person_titlesperson_senioritiesperson_locationsIf the ICP is vague, ask 1-2 clarifying questions before proceeding. At minimum, you need a title/role and an industry or company size.
Use mcp__claude_ai_Apollo_MCP__apollo_mixed_companies_search with the company filters:
q_organization_keyword_tags for industry/verticalorganization_num_employees_ranges for sizeorganization_locations for geographyper_page to 25Use mcp__claude_ai_Apollo_MCP__apollo_organizations_bulk_enrich with the domains from the top 10 results. This reveals revenue, funding, headcount, and firmographic data to help rank companies.
Use mcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_search with:
person_titles and person_seniorities from the ICPq_organization_domains_list scoped to the enriched company domainsper_page set to 25Credit warning: Tell the user exactly how many credits will be consumed before proceeding.
Use mcp__claude_ai_Apollo_MCP__apollo_people_bulk_match to enrich up to 10 leads per call with:
first_name, last_name, domain for each personreveal_personal_emails set to trueIf more than 10 leads, batch into multiple calls.
Show results in a ranked table:
| # | Name | Title | Company | Employees | Revenue | Phone | ICP Fit |
|---|
ICP Fit scoring:
Summary: Found X leads across Y companies. Z credits consumed.
Ask the user:
mcp__claude_ai_Apollo_MCP__apollo_contacts_create with run_dedupe: true for each lead/apollo:company-intel on any company from the listEmbed Zoom Virtual Agent chat on web with secure controls and context updates.
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