enrich-lead

Enrich Lead

Turn any identifier into a full contact dossier. The user provides identifying info via "$ARGUMENTS".

Lark-native note: Apollo stays the enrichment engine (it owns the data). Once a contact is enriched, the collaboration layer is Lark — log the lead to a Lark Base CRM (system-of-record), draft outreach as a Lark mail, and resolve any internal owner via lark_contact_search. See ../../connectors/LARK-PATTERNS.md (P1/P4/P5) for the handoff contract.

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, Lark Wiki
• /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. The first two stay in Apollo (its data, its sequences); the rest are the Lark collaboration layer.

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
5. Log to Lark CRM (Base) — Persist the enriched lead to a Lark Base as system-of-record (P5). First dedup-check with lark_base_search: it REQUIRES search_fields (the Bitable API mandates which field(s) to match on, e.g. the email or name column) and does NOT support jq — narrow with select_fields / limit instead. If you don't know the field names, discover them first via lark_api GET /open-apis/bitable/v1/apps/{base}/tables/{table}/fields. Then lark_base_record_upsert (base_token, table_id, fields: name, title, company, work/personal email, phone, location, LinkedIn, ICP notes) with dry_run: true; show the planned record, then commit. If no leads Base exists yet, scaffold one with the base-deploy skill rather than hand-rolling schema.
6. Draft outreach in Lark Mail — Draft (never auto-send) a first-touch email to the lead's work email with lark_mail_draft_create so the user reviews it in the Mail UI before sending. If an internal owner should be assigned, resolve them first with lark_contact_search to get their open_id. For the YAML/card grammar of a richer recap, delegate to the lark-mail / lark-im skills.