Find Contacts at Target Accounts

What this skill does

Takes a list of companies and returns ranked contacts at each one - searching by company (domain/name), with title, seniority, and department included on every row. Optionally enriches the resulting contact list with business emails and mobile numbers.

The output is a unified people list across all accounts, ready for outreach or CRM import.

Chain

company list
  to search_people  (per company, looped - optional seniority/department/country slice)
  to deduplicate
  to linkedin_to_business_email     (optional - per-URL parallel calls)
  to linkedin_to_mobile_phone              (optional - batch array)

Inputs

• Company list - names, names + domains, or CSV
• Optional role slice - seniority, department, or country to narrow contacts at each account
• Acceptable risk scores - which A-F deliverability grades to keep (recommended: A, B, C and F; D excluded)

How it works

1. Parses your company list and infers domains where possible
2. Confirms target count per company (default 3, max 25 per call)
3. Runs a free credit check before proceeding
4. Runs a probe search on the first company to verify result quality
5. Loops all companies, deduplicates, then optionally enriches

Output

Companies searched:   X
Contacts found:       X  (avg X per company)
Zero-result accounts: X
Business emails:      X/N  (XX%)
Credits used:         ~XXX

Email risk scores:
  A: X   B: X   C: X   D: X   F: X
  kept (accepted grades):  X
  filtered (excluded):     X

Zero-result companies are listed separately.

Search filters

search_people filters on query, company, company_domain, country, state, city, seniority, department or functional_area, industry, linkedin_industry, naics_code, employee_range, and revenue_range.

• Filters are free precision - execution cost comes from the free-text query, so a filters-only search runs ~40x cheaper and lands more precisely. A bare query is never the right shape; at minimum it gets country attached (~99% fill rate).
• Size and revenue apply to the person's current employer - "VPs at 51-200 employee software companies" is one call, not a company search followed by a people search.
• Three industry vocabularies - broad industry buckets, LinkedIn's ~150 niche labels, or a NAICS code at any depth. Shortening the code widens the net.
• Sparse filters are the usual cause of a thin result set - seniority/industry/department are ~60% filled and naics_code/linkedin_industry ~50%, and every filter is exact-match, silently dropping records where the field is empty.
• Sizing is free - count_only: true returns a match count without fetching data or charging tokens, and every response carries results.total to read before paginating.

Tips

• For 10+ companies, expect this to take a while - the skill reports progress periodically
• Credits run out mid-loop? Completed rows are output with the exact resume point
• Every returned email carries an A-F deliverability risk score; you're asked up front which grades to keep, and out-of-range grades are shown and flagged rather than silently dropped