PaperclipOrg
Claude Agent Skill · by Anthropics

Enrich Lead

Install Enrich Lead skill for Claude Code from anthropics/knowledge-work-plugins.

Install
Terminal · npx
$npx skills add https://github.com/obra/superpowers --skill brainstorming
Works with Paperclip

How Enrich Lead fits into a Paperclip company.

Enrich Lead drops into any Paperclip agent that handles this kind of work. Assign it to a specialist inside a pre-configured PaperclipOrg company and the skill becomes available on every heartbeat — no prompt engineering, no tool wiring.

S
SaaS FactoryPaired

Pre-configured AI company — 18 agents, 18 skills, one-time purchase.

$27$59
Explore pack
Source file
SKILL.md80 lines
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---name: enrich-leaddescription: "Instant lead enrichment. Drop a name, company, LinkedIn URL, or email and get the full contact card with email, phone, title, company intel, and next actions."user-invocable: trueargument-hint: "[name, company, LinkedIn URL, or email]"--- # Enrich Lead Turn any identifier into a full contact dossier. The user provides identifying info via "$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_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 flow3. **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 company4. **Find similar people** — Search for people with the same title/seniority at other companies