Execution Prompts · Apify

Check Apify MCP connection status. List all available actors related to
Google Maps scraping and LinkedIn profile scraping. Confirm the following
actors are available:

  - lukaskrivka/google-maps-with-contact-details
  - compass/crawler-google-places
  - harvestapi/linkedin-profile-search
  - dev_fusion/Linkedin-Profile-Scraper
  - apify/website-content-crawler

Report the actor IDs and current credit balance.

Run the Apify actor "lukaskrivka/google-maps-with-contact-details" with:

{
  "searchStringsArray": [
    "med spa near Kansas City MO 64154",
    "medical spa Kansas City Northland",
    "Botox clinic near Kansas City MO",
    "laser hair removal Kansas City MO",
    "CoolSculpting near Kansas City MO",
    "aesthetic clinic Kansas City MO",
    "skin care clinic near Platte County MO",
    "medspa near Overland Park KS"
  ],
  "maxCrawledPlacesPerSearch": 30,
  "scrapeEmails": true,
  "scrapeSocials": true,
  "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["SHADER"] }
}

Filter results within 15 miles of 39.2511104, -94.6316167.

# Score using the standard medical qualification matrix
# Output: markdown table → /scrape_results/03_med_spa.md

Run harvestapi/linkedin-profile-search with:

{
  "keywords": "practice owner OR medical director OR managing partner",
  "locations": ["Kansas City Metropolitan Area"],
  "industries": ["Hospital & Health Care", "Medical Practice"],
  "seniority": ["Owner", "Partner", "CXO", "Director"],
  "maxResults": 100
}

For each profile, extract: name, current title, current company,
company domain (if visible), location, profile URL.

Output: markdown table → /scrape_results/13_medical_practice_owners.md

After Phase 1 completes, take the top-20 highest-scoring practice domains.
Run apify/website-content-crawler with:

{
  "startUrls": [{{TOP_20_DOMAINS}}],
  "maxCrawlDepth": 2,
  "includeUrlGlobs": [
    "**/about**", "**/team**",
    "**/providers**", "**/contact**",
    "**/locations**"
  ]
}

For each domain, extract: staff names, titles, emails, location count.
Join to the Phase 1 business records by domain.

Output: /scrape_results/17_website_enrichment.md

After all 16 prompts above complete, consolidate every result into the
master medical prospect list.

# Steps
1. Read every file in /scrape_results/ (01–17)
2. Deduplicate by domain (case-insensitive)
3. Deduplicate by phone number (E.164 normalization)
4. Re-score using the standard scoring matrix
5. Apply tier (A / B / C / D)
6. Sort by score descending

# Outputs
  - /MASTER_MEDICAL_PROSPECT_LIST.md  (markdown)
  - /MASTER_MEDICAL_PROSPECT_LIST.csv  (csv for Clay)

# Final summary report
  - Total unique businesses
  - Total by category
  - Total by tier
  - Total with email
  - Total with website
  - Top-25 hottest prospects with full detail