enrich-lead
anthropics/knowledge-work-plugins
Instant lead enrichment from any identifier—name, email, LinkedIn, or company.
What is enrich-lead?
Enrich-lead transforms a single identifier (name, email, LinkedIn URL, or company) into a complete contact dossier with verified email, phone, title, company intelligence, and recommended next actions. Use it when you need to quickly gather comprehensive prospect or contact information for sales, recruiting, or business development.
- Parse any identifier (name, email, LinkedIn URL, company, or job title) and extract matching signals
- Match and enrich person records with verified contact details including work/personal emails and phone numbers
- Retrieve company firmographics (industry, employee count, revenue, funding, HQ location)
- Present a formatted contact card with all enriched fields
- Suggest follow-up actions: save to Apollo, add to sequence, find colleagues, or find similar prospects
How to install enrich-lead
npx skills add https://github.com/anthropics/knowledge-work-plugins --skill enrich-lead- Apollo account with available credits (each enrichment consumes 1 credit)
- Valid identifier input: name, email, LinkedIn URL, company name, or job title
How to use enrich-lead
- 1.Invoke the skill with an identifier: name, email, LinkedIn URL, company, or job title
- 2.Review the credit warning and confirm you want to proceed
- 3.Wait for the skill to parse your input and match the person record
- 4.Review the formatted contact card with email, phone, title, company details, and location
- 5.Choose a next action: save to Apollo, add to sequence, find colleagues, or find similar people
Use cases
- Sales rep discovers a prospect's name and company, runs enrichment to get direct email and phone for outreach
- Recruiter finds a LinkedIn profile and enriches it to get verified contact info and company context before reaching out
- Business development team identifies a CEO title and company name, enriches to confirm identity and get firmographic data for partnership discussions
- User has only an email address and needs full contact details plus company intelligence to personalize an outreach campaign
- Team member finds a prospect on LinkedIn and enriches to populate CRM with complete contact card before adding to a sales sequence
- Sales development representatives
- Account executives
- Recruiters and talent acquisition teams
- Business development professionals
- Marketing teams running targeted outreach campaigns
enrich-lead FAQ
A name, company name, email address, LinkedIn URL, job title, or any combination. Examples: 'Tim Zheng at Apollo', 'sarah@stripe.com', 'https://www.linkedin.com/in/timzheng', or 'CEO of Figma'.
The skill will search for the top 3 candidate matches and ask you to pick the correct person, then re-enrich with that selection.
Yes, the skill requests personal email revelation when available, so you get both work and personal contact options.
Each enrichment consumes 1 Apollo credit. The skill warns you before proceeding.
Yes. After enrichment, you can select 'Find colleagues' to search for other people at that company using the company domain.
Full instructions (SKILL.md)
Source of truth, from anthropics/knowledge-work-plugins.
name: enrich-lead description: "Instant lead enrichment. Drop a name, company, LinkedIn URL, or email and get the full contact card with email, phone, title, company intel, and next actions." user-invocable: true argument-hint: "[name, company, LinkedIn URL, or email]"
Enrich Lead
Turn any identifier into a full contact dossier. The user provides identifying info via "$ARGUMENTS".
Examples
/apollo:enrich-lead Tim Zheng at Apollo/apollo:enrich-lead https://www.linkedin.com/in/timzheng/apollo:enrich-lead sarah@stripe.com/apollo:enrich-lead Jane Smith, VP Engineering, Notion/apollo:enrich-lead CEO of Figma
Step 1 — Parse Input
From "$ARGUMENTS", extract every identifier available:
- First name, last name
- Company name or domain
- LinkedIn URL
- Email address
- Job title (use as a matching hint)
If the input is ambiguous (e.g. just "CEO of Figma"), first use mcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_search with relevant title and domain filters to identify the person, then proceed to enrichment.
Step 2 — Enrich the Person
Credit warning: Tell the user enrichment consumes 1 Apollo credit before calling.
Use mcp__claude_ai_Apollo_MCP__apollo_people_match with all available identifiers:
first_name,last_nameif name is knowndomainororganization_nameif company is knownlinkedin_urlif LinkedIn is providedemailif email is provided- Set
reveal_personal_emailstotrue
If the match fails, try mcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_search with looser filters and present the top 3 candidates. Ask the user to pick one, then re-enrich.
Step 3 — Enrich Their Company
Use mcp__claude_ai_Apollo_MCP__apollo_organizations_enrich with the person's company domain to pull firmographic context.
Step 4 — Present the Contact Card
Format the output exactly like this:
[Full Name] | [Title] [Company Name] · [Industry] · [Employee Count] employees
| Field | Detail |
|---|---|
| Email (work) | ... |
| Email (personal) | ... (if revealed) |
| Phone (direct) | ... |
| Phone (mobile) | ... |
| Phone (corporate) | ... |
| Location | City, State, Country |
| URL | |
| Company Domain | ... |
| Company Revenue | Range |
| Company Funding | Total raised |
| Company HQ | Location |
Step 5 — Offer Next Actions
Ask the user which action to take:
- Save to Apollo — Create this person as a contact via
mcp__claude_ai_Apollo_MCP__apollo_contacts_createwithrun_dedupe: true - Add to a sequence — Ask which sequence, then run the sequence-load flow
- Find colleagues — Search for more people at the same company using
mcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_searchwithq_organization_domains_listset to this company - Find similar people — Search for people with the same title/seniority at other companies
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