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Enrich Person

/enrich-person

Enrich a person from a name, email or LinkedIn URL and get back their job title, company and contact details for 1 credit.

Download Skillenrich-person.zip · free

Overview

enrich-person calls the SyncGTM MCP enrich_person tool to turn one identifier for a person — first and last name, email, LinkedIn URL or company — into a fuller record with job title, company and contact details. Every call costs 1 credit no matter how many identifiers you send, so passing the company name alongside a name is free accuracy. It is the general-purpose person lookup: for work history, education and skills, use linkedin_profile_enrich instead.

What it does

  1. 1

    Takes at least one identifier — first_name and last_name, email, linkedin_url or organization_name — and returns the person behind it

  2. 2

    Anchors on the strongest identifier you hold: linkedin_url and email beat a bare name, and every extra identifier you pass narrows the match

  3. 3

    Returns first_name, last_name, job_title, email and organization_name, so a form-fill row with nothing but an address becomes a named contact with a title

  4. 4

    Treats organization_name as the accuracy setting that matters — a common name with no company attached is the main cause of a wrong match, and a wrong match still bills

  5. 5

    Does not return phone numbers, work history, education or skills, and cannot search for someone you cannot already name. It also returns no LinkedIn URL and no company domain, so chaining into find_work_email (needs linkedin_url) or enrich_organization (needs domain) means resolving that key elsewhere first

  6. 6

    Costs 1 credit per call, whether you send one identifier or all five

How to use it

  1. 1

    Download the skill file — it saves as enrich-person.zip.

  2. 2

    In Claude, open Settings → Capabilities → Skills and upload the .zip (or unzip the enrich-person/ folder into .claude/skills/ for Claude Code).

  3. 3

    Connect the SyncGTM MCP server at docs.syncgtm.com/mcp_server/setup — browser sign-in, no API key — then run check_credits (free) to confirm your balance.

  4. 4

    Trigger it by typing /enrich-person and pasting a name and company, an email, a LinkedIn URL, or a CSV column of any of those.

  5. 5

    Tune the two things that change the result: pass organization_name on every call so a common name resolves to the right person, and cap the batch — 'stop after 50 rows and report credits used' so a long paste cannot outrun your balance.

Use cases

Complete CRM records

Fill the missing job title and company on contacts that arrived from a form with an email and nothing else. One call per row, 1 credit each.

Triage trial signups

Work out who actually signed up over the weekend before Monday standup, and split the list into buyers, end users and out-of-ICP.

Clean an event list

Turn a webinar or conference export of names and companies into titled contacts, so you only chase the attendees on the buying committee.

Identify an unknown replier

Someone replies from an address you do not recognize. Enrich the email to get their name, title and employer before you write back.

GTM workflow examples

Turn a webinar attendee list into a follow-up shortlist

  1. 1Paste the attendee export (first name, last name, company, registration email) and call `enrich_person` once per row with `organization_name` set, filling job_title and organization_name at 1 credit a row.
  2. 2Keep only the rows whose job_title sits on the buying committee — VP Sales, RevOps, Head of Growth — and drop individual contributors and students before spending anything further.
  3. 3Call `enrich_organization` (2 credits) on each surviving company's domain — take the domain from the registration email, since this tool accepts `domain` only and never a company name — then cut accounts under your headcount floor.
  4. 4For rows whose enriched record came back without an address, call `find_people_within_company` (1.5 credits, `domain` plus a `job_title` array) to get the person's LinkedIn URL, then `find_work_email` (1 credit) on that `linkedin_url` — find_work_email takes nothing else as its anchor.
  5. 5Call `verify_email` (0.3 credits) across the shortlist to remove undeliverables before anything loads into a sequence.

Outcome: A follow-up shortlist of ICP-matching attendees, each carrying a job title, a qualified company and a verified work email, ready to load into a sequence the same day.

Monday triage of the weekend's trial signups

  1. 1Take the signup export — most rows are an email address and a timestamp — and call `enrich_person` anchored on `email`, capped at the row count, 1 credit each.
  2. 2Read job_title and organization_name off each result and split the list into three buckets: buyers, end users, and out-of-ICP.
  3. 3Call `enrich_organization` (2 credits) on the domain from each buyer's signup email, skipping free-mail domains, so a 4-person agency does not get the same treatment as a 900-person insurer.
  4. 4Call `find_people_within_company` (1.5 credits) on the domains where the signup is an end user, with `job_title` set to ["VP Sales", "Director of Sales", "Head of RevOps"], to surface the director or VP above them.
  5. 5Call `verify_email` (0.3 credits) on every address before the sequence, and mark unverified rows for manual review.

Outcome: A triage table for standup: every weekend signup named, titled and scored by company size, plus the named decision-maker to loop in on each account where the signup cannot buy.

Refresh a stale CRM segment before a quarterly campaign

  1. 1Export the contacts untouched for 12 months, deduplicate on lowercased email, cap the run at 200 rows, and call `check_credits` (free) to price it at 1 credit a row.
  2. 2Call `enrich_person` on each row anchored on the stored email, then compare the returned job_title and organization_name against what the CRM holds.
  3. 3Flag every row where the returned company disagrees with the CRM — those are the people who left — and call `find_linkedin_from_work_email` (2 credits) on that subset only, because the next tool needs a profile URL and enrich_person does not return one.
  4. 4Call `check_job_change` (2 credits) with each `profile_url` to confirm the move and get the new company.
  5. 5Call `find_work_email` (1 credit) on each mover's `linkedin_url` for a working address at the new employer, then `verify_email` (0.3 credits) before anything sends.

Outcome: A corrected CRM segment with current titles and companies, plus a separate movers list carrying each person's new employer and a verified work email for a re-entry campaign.

Prompts

Paste any of these into Claude once the skill is installed and the SyncGTM MCP is connected.

Enrich Jane Doe at Stripe and return just her job title, company and email.
Who is behind jane@stripe.com? Give me the name, job title and company.
Enrich https://www.linkedin.com/in/janedoe/ and tell me her current title and employer.
Here are 40 rows with first name, last name and company. Enrich all of them, pass organization_name on every call, stop after 40 rows, and report credits used plus which rows came back empty.
Enrich these 25 trial signup emails, stop after 25 rows so the run cannot cost more than 25 credits, and flag any row that comes back with no job title or no company.

Best practices

  • Always pass organization_name. One call is 1 credit however many identifiers you send, and a bare common name is the single biggest cause of a wrong match.

  • Anchor on the strongest identifier you hold: linkedin_url first, then email, then first_name plus last_name. Treat a name-only anchor as a last resort.

  • Spot-check the first three rows of any batch before letting it run. A wrong match bills the same credit as a right one, and it is far cheaper to catch at row 3 than at row 200.

  • Cap every batch and run check_credits (free) first. 'Stop after 50 and report credits used' is the difference between a priced run and a surprise.

  • Say which fields you want back. 'Just the job title and company' keeps the client from printing the entire record into the chat.

  • Pick the right sibling and feed it the right key: linkedin_profile_enrich (1 credit) for work history, education and skills; find_work_email (1 credit) when you already hold the linkedin_url it requires; find_people (0.3 credits per result, always with an explicit limit) when you cannot name the person yet. This tool returns organization_name, not a domain or a profile URL, so enrich_organization (domain) and check_job_change (profile_url) need that key resolved before you call them.

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Ready to run /enrich-person on your own data?