Email addresses to LinkedIn profiles

When to use

• The user has a list of customers or sign-ups and wants their LinkedIn profiles to connect or research.
• "Who are these people?" for a batch of emails.
• Use email_to_linkedin when only the URL is needed. Use reverse_email_lookup when the user also wants title, company and location.

Before you start

1. Check the connection: call get_account with {} or run npx ravn whoami.
2. email_to_linkedin and reverse_email_lookup need your own provider key connected — run ravn keys add pdl first; these tools run on your own provider account. If a tool returns 403 provider_key_required, stop and tell the human to add their key. Every call is one lookup; misses are free.
3. Ask which output the user needs. Both tools are one lookup per call, so if there is any chance they want title or company, reverse_email_lookup gives more for the same cost.

Steps

1. Clean the list locally: trim, lowercase, remove duplicates and obvious junk.
2. Optional but useful for big lists: run validate_emails first (ours, 1 lookup each) and skip addresses that are invalid or disposable. Those rarely match a real profile.

{ "emails": ["jane@acme.com", "sam@brightpath.io"] }

1. URL only, one address:

{ "email": "jane@acme.com" }

email_to_linkedin returns email, linkedin_url and full_name. 4. Full profiles, up to 100 per call over MCP:

{ "emails": ["jane@acme.com", "sam@brightpath.io"] }

reverse_email_lookup returns one item per address with its own status and a result holding full_name, title, headline, seniority, city, state, country, industry, linkedin_url, company and last_updated_at. Its business_email is re-verified. 5. A CSV with the CLI: dry run, sample, full.

npx ravn enrich customers.csv --tool email_to_linkedin --column Email --dry-run
npx ravn enrich customers.csv --tool email_to_linkedin --column Email --limit 10 --out sample.csv
npx ravn enrich customers.csv --tool email_to_linkedin --column Email --out with-linkedin.csv

Swap in --tool reverse_email_lookup for full profiles. The dry run shows how many lookups the run will use. 6. Check the match. If full_name clearly does not fit the name the user already has for that row, flag it as match_check: review rather than trusting it. 7. Free-provider addresses (Gmail and similar) match less often. Say so in the summary rather than retrying.

Output

The CSV keeps every original column and adds:

• rw_status: ok, not_found, error or dropped.
• For email_to_linkedin: rw_email, rw_linkedin_url, rw_full_name.
• For reverse_email_lookup: rw_full_name, rw_title, rw_seniority, rw_city, rw_state, rw_country, rw_industry, rw_linkedin_url, rw_company (JSON), rw_last_updated_at.
• match_check where you flagged a name mismatch.

Summary: emails in, profiles found, match rate for work versus free-provider addresses, and lookups used.

Rules

• Ravn does not scrape LinkedIn; profiles come from your own data-provider account, and opted-out people are never returned. Do not try to find them another way. See /privacy#optout.
• No FCRA uses: never look up applicants, tenants or candidates to decide credit, employment, insurance or housing.
• Use profiles for business context and outreach only.
• On a 429 fair_use_exhausted or a 403 provider_key_required, stop and tell the human.

Example prompt

Here's a CSV of our 300 paying customers' emails. Find their LinkedIn profiles and job titles so our CS team knows who they're talking to.