Enrich Lead
This is the Apollo enrichment workflow distilled into a single command. You drop a name, email, LinkedIn URL, or even something vague like "CEO of Figma" and get back a formatted contact card with work email, personal email if available, phone numbers, title, and full company intel including revenue and funding. It burns one Apollo credit per lookup and warns you before it does. The real utility is in what happens after: you can save the contact directly to Apollo with deduplication, add them to a sequence, or immediately pivot to finding their colleagues or similar people at other companies. It's faster than clicking through the Apollo UI when you're already in a Claude conversation doing research or list building.
- installs
- 2.9K
- GitHub stars
- 33.3K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add anthropics/knowledge-work-plugins --skill enrich-lead --agent claude-codeInstalls into .claude/skills of the current project.
Files
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
Sponsors
Details
- Repository
- github.com/anthropics/knowledge-work-plugins
- Category
- Sales & Marketing
- First seen
- Apr 16, 2026
