---
id: daily-prospect
name: "prospect"
url: https://skills.yangsir.net/skill/daily-prospect
author: anthropics
domain: sales
tags: ["lead-generation", "sales-intelligence", "crm", "b2b-sales", "prospecting"]
install_count: 1200
rating: 4.30 (24 reviews)
github: https://github.com/anthropics/knowledge-work-plugins
---

# prospect

> 从理想客户画像描述直接生成排序、丰富的潜在客户列表，支持精细筛选和联系人信息

**Stats**: 1,200 installs · 4.3/5 (24 reviews)

## Before / After 对比

### 客户开发效率

**Before**:

手动搜索LinkedIn、筛选公司、查找决策人邮箱，整理10个线索需要2-3小时

**After**:

描述ICP自动生成排序潜在客户列表，15分钟获得50个高质量 enriched 线索

| Metric | Before | After | Change |
|---|---|---|---|
| 开发效率 | 15min/lead | 2min/lead | -86.7% |

## Readme

# prospect

# Prospect

Go from an ICP description to a ranked, enriched lead list in one shot. The user describes their ideal customer via "$ARGUMENTS".

## Examples

- `/apollo:prospect VP of Engineering at Series B+ SaaS companies in the US, 200-1000 employees`

- `/apollo:prospect heads of marketing at e-commerce companies in Europe`

- `/apollo:prospect CTOs at fintech startups, 50-500 employees, New York`

- `/apollo:prospect procurement managers at manufacturing companies with 1000+ employees`

- `/apollo:prospect SDR leaders at companies using Salesforce and Outreach`

## Step 1 — Parse the ICP

Extract structured filters from the natural language description in "$ARGUMENTS":

**Company filters:**

- Industry/vertical keywords → `q_organization_keyword_tags`

- Employee count ranges → `organization_num_employees_ranges`

- Company locations → `organization_locations`

- Specific domains → `q_organization_domains_list`

**Person filters:**

- Job titles → `person_titles`

- Seniority levels → `person_seniorities`

- Person locations → `person_locations`

If the ICP is vague, ask 1-2 clarifying questions before proceeding. At minimum, you need a title/role and an industry or company size.

## Step 2 — Search for Companies

Use `mcp__claude_ai_Apollo_MCP__apollo_mixed_companies_search` with the company filters:

- `q_organization_keyword_tags` for industry/vertical

- `organization_num_employees_ranges` for size

- `organization_locations` for geography

- Set `per_page` to 25

## Step 3 — Enrich Top Companies

Use `mcp__claude_ai_Apollo_MCP__apollo_organizations_bulk_enrich` with the domains from the top 10 results. This reveals revenue, funding, headcount, and firmographic data to help rank companies.

## Step 4 — Find Decision Makers

Use `mcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_search` with:

- `person_titles` and `person_seniorities` from the ICP

- `q_organization_domains_list` scoped to the enriched company domains

- `per_page` set to 25

## Step 5 — Enrich Top Leads

**Credit warning**: Tell the user exactly how many credits will be consumed before proceeding.

Use `mcp__claude_ai_Apollo_MCP__apollo_people_bulk_match` to enrich up to 10 leads per call with:

- `first_name`, `last_name`, `domain` for each person

- `reveal_personal_emails` set to `true`

If more than 10 leads, batch into multiple calls.

## Step 6 — Present the Lead Table

Show results in a ranked table:

### Leads matching: [ICP Summary]

#
Name
Title
Company
Employees
Revenue
Email
Phone
ICP Fit

**ICP Fit** scoring:

- **Strong** — title, seniority, company size, and industry all match

- **Good** — 3 of 4 criteria match

- **Partial** — 2 of 4 criteria match

**Summary**: Found X leads across Y companies. Z credits consumed.

## Step 7 — Offer Next Actions

Ask the user:

- **Save all to Apollo** — Bulk-create contacts via `mcp__claude_ai_Apollo_MCP__apollo_contacts_create` with `run_dedupe: true` for each lead

- **Load into a sequence** — Ask which sequence and run the sequence-load flow for these contacts

- **Deep-dive a company** — Run `/apollo:company-intel` on any company from the list

- **Refine the search** — Adjust filters and re-run

- **Export** — Format leads as a CSV-style table for easy copy-paste

Weekly Installs217Repository[anthropics/know…-plugins](https://github.com/anthropics/knowledge-work-plugins)GitHub Stars10.0KFirst SeenFeb 24, 2026Security Audits[Gen Agent Trust HubPass](/anthropics/knowledge-work-plugins/prospect/security/agent-trust-hub)[SocketPass](/anthropics/knowledge-work-plugins/prospect/security/socket)[SnykPass](/anthropics/knowledge-work-plugins/prospect/security/snyk)Installed oncodex205gemini-cli204cursor203opencode203github-copilot202amp202

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