Enrich Lead
Turn a name, company, LinkedIn URL, or email into a full contact dossier with verified channels and company context for outbound sales.
Overview
Enrich Lead is an agent skill for the Grow phase that turns a name, company, LinkedIn URL, or email into a full Apollo-enriched contact card with next-action context.
Install
npx skills add https://github.com/anthropics/knowledge-work-plugins --skill enrich-leadWhat is this skill?
- Parses mixed inputs: name, company, LinkedIn URL, email, or title-only hints like CEO of Figma
- Two-step flow: ambiguous title searches via mixed people search, then people match enrichment
- Surfaces credit use (1 Apollo credit) before calling enrichment
- Sets reveal_personal_emails on people match for fuller contact cards
- User-invocable slash-style entry with argument-hint for quick dossiers
- 1 Apollo credit per enrichment call (documented warning before match)
Adoption & trust: 1.6k installs on skills.sh; 19.6k GitHub stars; 3/3 security scanners passed (skills.sh audits).
What problem does it solve?
You only have a partial lead identifier and no reliable email, phone, or firmographic detail to personalize outreach.
Who is it for?
Solo builders doing B2B outbound or partnership outreach who already use Apollo MCP and accept per-enrichment credits.
Skip if: Teams without Apollo access, bulk list building without credits, or pure product analytics workflows unrelated to contact enrichment.
When should I use this skill?
User provides a name, company, LinkedIn URL, or email and wants full contact enrichment via Apollo.
What do I get? / Deliverables
You get a complete contact dossier from Apollo people match so you can draft outreach or CRM updates without manual lookup.
- Parsed identifier set
- Apollo people match dossier
- Suggested next actions for outreach
Recommended Skills
Journey fit
Lead enrichment sits in Grow because solo builders use it after they have something to sell—prospecting, follow-ups, and pipeline hygiene—not during initial idea research. Lifecycle is the canonical shelf for turning identifiers into actionable contact records and next-step outreach cues.
How it compares
Use instead of hand-copying LinkedIn snippets when you need structured Apollo match fields in one agent turn.
Common Questions / FAQ
Who is enrich-lead for?
Solo and indie builders who sell SaaS or services and need fast, structured prospect cards from minimal input via Claude with Apollo MCP.
When should I use enrich-lead?
Use it in Grow (lifecycle) when you have a name, domain, LinkedIn URL, or email and need verified contact and company fields before emailing or logging CRM notes.
Is enrich-lead safe to install?
It calls external Apollo APIs and may reveal personal emails; review the Security Audits panel on this page and your Apollo data-handling policy before enabling it in production agents.
SKILL.md
READMESKILL.md - Enrich Lead
# 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_name` if name is known - `domain` or `organization_name` if company is known - `linkedin_url` if LinkedIn is provided - `email` if email is provided - Set `reveal_personal_emails` to `true` 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: 1. **Save to Apollo** — Create this person as a contact via `mcp__claude_ai_Apollo_MCP__apollo_contacts_create` with `run_dedupe: true` 2. **Add to a sequence** — Ask which sequence, then run the sequence-load flow 3. **Find colleagues** — Search for more people at the same company using `mcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_search` with `q_organization_domains_list` set to this company 4. **Find similar people** — Search for people with the same title/seniority at other companies