---
id: daily-enrich-lead
name: "enrich-lead"
url: https://skills.yangsir.net/skill/daily-enrich-lead
author: anthropics
domain: sales
tags: ["lead-enrichment", "sales-intelligence", "crm", "lead-generation", "b2b-sales"]
install_count: 1300
rating: 4.30 (20 reviews)
github: https://github.com/anthropics/knowledge-work-plugins
---

# enrich-lead

> 将任意标识符（邮箱、LinkedIn等）转化为完整联系人档案，辅助销售精准获客

**Stats**: 1,300 installs · 4.3/5 (20 reviews)

## Before / After 对比

### 线索调研效率

**Before**:

手动搜索LinkedIn和公司官网，信息分散不全，调研一个线索需要20分钟

**After**:

输入任意标识符自动聚合完整档案，决策人背景一清二楚

| Metric | Before | After | Change |
|---|---|---|---|
| 调研时间 | 20min | 2min | -90% |

## Readme

# 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:

- **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

Weekly Installs215Repository[anthropics/know…-plugins](https://github.com/anthropics/knowledge-work-plugins)GitHub Stars9.9KFirst SeenFeb 24, 2026Security Audits[Gen Agent Trust HubPass](/anthropics/knowledge-work-plugins/enrich-lead/security/agent-trust-hub)[SocketPass](/anthropics/knowledge-work-plugins/enrich-lead/security/socket)[SnykPass](/anthropics/knowledge-work-plugins/enrich-lead/security/snyk)Installed oncodex202opencode202gemini-cli201cursor200github-copilot200amp200

---
*Source: https://skills.yangsir.net/skill/daily-enrich-lead*
*Markdown mirror: https://skills.yangsir.net/api/skill/daily-enrich-lead/markdown*