Knowledge-work-plugins enrich-lead

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

source · Clone the upstream repo

git clone https://github.com/anthropics/knowledge-work-plugins

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/anthropics/knowledge-work-plugins "$T" && mkdir -p ~/.claude/skills && cp -r "$T/partner-built/apollo/skills/enrich-lead" ~/.claude/skills/anthropics-knowledge-work-plugins-enrich-lead && rm -rf "$T"

manifest: partner-built/apollo/skills/enrich-lead/SKILL.md

source content

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:

Save to Apollo — Create this person as a contact via

mcp__claude_ai_Apollo_MCP__apollo_contacts_create

with

run_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_search
```
with
```
q_organization_domains_list
```
set to this company
Find similar people — Search for people with the same title/seniority at other companies