anthropics/enrich-lead
partner-built/apollo/skills/enrich-lead/SKILL.md
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.
$ install --global
skillsauthnpx skillsauth add anthropics/knowledge-work-plugins enrich-leadInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Error
VirusTotalMulti-engine malware detection
70%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Mar 25, 2026, 9:41 PM45.1s1 file scanned
SKILL.md
- 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 "$ARGUMENTS".
Examples
/apollo:enrich-lead Tim Zheng at Apollo/apollo:enrich-lead https://www.linkedin.com/in/timzheng/apollo:enrich-lead [email protected]/apollo:enrich-lead Jane Smith, VP Engineering, Notion/apollo:enrich-lead CEO of Figma
Step 1 — Parse Input
From "$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 | | LinkedIn | 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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