build-targeted-lead-list

name	build-targeted-lead-list
description	End-to-end workflow to search for prospects, preview results, refine criteria, and create a confirmed lead list in Amplemarket.
metadata	{"author":"amplemarket","version":"1.0.4","category":"Prospecting & Lead Generation"}
compatibility	Requires Amplemarket MCP server

Build Targeted Lead List

End-to-end workflow to search for prospects, preview results, refine criteria, and create a confirmed lead list in Amplemarket.

Instructions

Guide the user through building a lead list from scratch. This is a multi-step, interactive workflow.

Steps

1. Gather search criteria from the user. Ask for any of:

   • Target titles and seniority levels
   • Target departments or job functions
   • Person locations
   • Company names, domains, industries, sizes, or types
   • Any other qualifying criteria

   If the user gives a broad description, parse it into structured filters (see the prospect-icp-search skill for mapping guidance).

2. Resolve enum values by calling:

   • mcp__claude_ai_Amplemarket__get_industries to match industry terms to valid API values.
   • mcp__claude_ai_Amplemarket__get_job_functions to match job function terms to valid API values.

3. Execute the search by calling mcp__claude_ai_Amplemarket__search_people with the mapped parameters. Set full_output to true and page_size to 20 for the preview.

4. Present a preview of the results to the user:

   • Show the first 10-20 results in a table (Name, Title, Company, Location).
   • Report the total number of matching prospects.
   • Ask: "Does this look right? Would you like to refine the search or proceed with creating the list?"

5. Refine if needed. If the user wants changes:

   • Adjust filters based on feedback.
   • Re-run mcp__claude_ai_Amplemarket__search_people with updated parameters.
   • Show the updated preview.
   • Repeat until the user approves.

6. Collect all results once approved. If total results exceed one page, paginate through all pages using the page parameter to gather all LinkedIn URLs (up to the 10,000 lead limit).

7. Ask for list configuration:

   • List name (suggest a descriptive default like "VP Sales - Fintech - NYC - Mar 2026")
   • List type - determine based on available data:
     • "linkedin" if leads have LinkedIn URLs
     • "email" if leads have email addresses
     • "titles_and_company" if leads have title + company domain
   • Enrichment options: Ask if they want to enable (note: each option consumes additional Amplemarket credits per lead):
     • Email enrichment (enrich: true)
     • Email validation (validate_email: true)
     • Phone number reveal (reveal_phone_numbers: true)
   • Inform the user of the credit implications before enabling enrichment: "Enabling enrichment will use credits for each lead. For a list of [N] leads, that's [N] enrichment credits. Want to proceed?"

8. Create the lead list by calling mcp__claude_ai_Amplemarket__create_lead_list with:

   • type: determined list type
   • name: chosen name
   • leads: array of lead objects (with linkedin_url, email, or title + company_domain depending on type)
   • options: enrichment settings

   If total leads exceed the batch that fits in a single create call, use mcp__claude_ai_Amplemarket__add_leads_to_lead_list to add remaining leads to the created list using the returned lead_list_id.

9. Confirm creation with the user:

   • Lead list ID
   • Total leads added
   • Enrichment settings enabled
   • Estimated processing time

Important Notes

• The leads array in create_lead_list supports a maximum of 10,000 entries.
• Always show a preview before creating the list. Never create without user confirmation.
• When using add_leads_to_lead_list, include the lead_list_id from the create response.
• If the user provides a ready-made list of LinkedIn URLs or emails, skip the search step and go directly to list creation.

Examples

Example 1: Full Workflow from Search to List

User prompt: "Build me a lead list of engineering managers at healthcare companies in the US with 500-5000 employees"

What the skill does:

1. Calls mcp__claude_ai_Amplemarket__get_industries to resolve healthcare industry values.
2. Calls mcp__claude_ai_Amplemarket__search_people with:

• person_titles: ["Engineering Manager"]
• person_seniorities: ["Manager"]
• person_departments: ["Engineering & Technical"]
• person_locations: ["United States"]
• company_industries: [matched healthcare values]
• company_sizes: ["501-1000 employees", "1001-5000 employees"]
• full_output: true, page_size: 20

3. Presents preview table and total count.
4. On user approval, collects all results across pages.
5. Calls mcp__claude_ai_Amplemarket__create_lead_list with:

• type: "linkedin"
• name: "Eng Managers - Healthcare US - 500-5K - Mar 2026"
• leads: [{"linkedin_url": "..."}, ...]
• options: {"enrich": true, "validate_email": true}

Example confirmation:

Lead list created successfully.

Detail	Value
List ID	lst_abc123def456
List Name	Eng Managers - Healthcare US - 500-5K - Mar 2026
Total Leads	312
Type	LinkedIn
Enrichment	Enabled
Email Validation	Enabled
Status	Processing

Your list is now being enriched. You can check its status anytime.

Example 2: Quick List from Existing URLs

User prompt: "Create a lead list called 'Q1 Targets' from these LinkedIn URLs: linkedin.com/in/user1, linkedin.com/in/user2, linkedin.com/in/user3"

What the skill does:

1. Skips search since the user has provided leads directly.
2. Calls mcp__claude_ai_Amplemarket__create_lead_list with:

• type: "linkedin"
• name: "Q1 Targets"
• leads: [{"linkedin_url": "https://linkedin.com/in/user1"}, {"linkedin_url": "https://linkedin.com/in/user2"}, {"linkedin_url": "https://linkedin.com/in/user3"}]
• options: {"enrich": true, "validate_email": true, "reveal_phone_numbers": true}

Example 3: Refined Search Workflow

User prompt: "Put together a list of senior marketing people at Series B+ SaaS companies in Europe"

What the skill does:

1. Resolves industries via mcp__claude_ai_Amplemarket__get_industries.
2. Runs initial search with person_seniorities: ["Senior", "Manager", "Director", "VP", "Head"], person_departments: ["Marketing"], person_locations: ["United Kingdom", "Germany", "France", "Netherlands", "Sweden", ...], matched SaaS industries.
3. Shows preview. User says "too many junior people, only Directors and above."
4. Re-runs with person_seniorities: ["Director", "VP", "Head", "C-Suite"].
5. Shows updated preview. User approves.
6. Creates list with all results.

Troubleshooting

Problem	Solution
Too many results to fit in one list	Paginate through results and use mcp__claude_ai_Amplemarket__add_leads_to_lead_list for batches after the first create call.
List creation fails	Verify that leads array format matches the list type. LinkedIn lists need linkedin_url, email lists need email, titles_and_company lists need title + company_domain.
Search returns irrelevant results	Tighten filters progressively: 1) Add person_seniorities to exclude junior titles. 2) Add person_departments to restrict to relevant functions. 3) Add company_sizes if results include wrong-size companies. Show the user a preview after each refinement so they can confirm the direction.
User wants to add to existing list	Use mcp__claude_ai_Amplemarket__list_lead_lists to find the existing list, then mcp__claude_ai_Amplemarket__add_leads_to_lead_list with its ID.
Enrichment not working	Check that the options object is correctly structured with boolean values for enrich, validate_email, and reveal_phone_numbers.
search_companies returns 0 results for a known company	Fallback chain: 1) Try searching by company domain instead of name. 2) Try enrich_company with the domain directly, as some companies are enrichable but not searchable by name. 3) Try parent company domain or alternate domains.
Search returns results but list creation fails	Verify that the leads array format matches the list type. LinkedIn lists need linkedin_url, email lists need email.