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prospect

Generate ranked decision-maker leads from natural-language ICP descriptions using Apollo data.

1|Updated Mar 30, 2026
Search Tags:#prospecting#apollo#b2b#icp#lead-scoring#lead-enrichment#contact-discovery
One-click install
npx skills add https://github.com/ilove323/comlan-skills --skill prospect-ilove323
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prospect
Source: https://github.com/ilove323/comlan-skills/tree/main/partner-built/apollo/skills/prospect
Command: npx skills add https://github.com/ilove323/comlan-skills --skill prospect-ilove323

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Convert a free-text ideal-customer profile (ICP) into an actionable, ranked list of decision-maker leads with contact information, removing manual company search and enrichment overhead.

Core Features & Use Cases

  • Parse natural-language ICP into structured company and person filters (industry keywords, employee ranges, locations, titles, seniorities).
  • Search and rank companies using Apollo-backed queries, then bulk-enrich top organizations for firmographics and revenue data.
  • Discover and batch-enrich people tied to enriched company domains, revealing emails and phone numbers while reporting credit consumption.
  • Produce a ranked table of contacts with ICP-match scoring and offer follow-up actions: save to Apollo, add to outreach sequences, run company deep-dives, or export CSV.

Quick Start

Use the prospect skill to find VP of Engineering at Series B+ SaaS companies in the US with 200-1000 employees and return a ranked table of contacts including emails and phone numbers.

Frequently Asked Questions about prospect

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate B2B leads from a natural language ICP description?▼

B2B lead generation from a natural language ICP parses your text into structured company and person filters, searches Apollo for matching organizations, and outputs a ranked list of enriched decision-maker contacts.

How does Apollo lead enrichment reveal contact information for prospective buyers?▼

Apollo lead enrichment executes bulk queries on discovered company domains to reveal decision-maker emails and phone numbers, while reporting your credit consumption throughout the contact discovery process.

Can I search for specific seniorities and employee ranges when building outbound prospect lists?▼

Searching for specific seniorities and employee ranges is supported by parsing your free-text ICP into structured company and person filters, enabling targeted B2B outbound research queries.

What is the best way to rank and prioritize discovered contacts for outreach sequences?▼

Ranking and prioritizing contacts for outreach applies ICP-match scoring to enriched profiles, producing a ranked table that you can directly add to Apollo outreach sequences or export as CSV.

Do I need an Apollo account to use automated contact discovery and firmographics enrichment?▼

An Apollo account is required to perform automated contact discovery and firmographics enrichment, as the process queries Apollo-backed data to retrieve company revenue details and reveal contact information.

What are the limitations of batched company and people searches for B2B prospecting?▼

Limitations of batched B2B prospecting searches include credit consumption limits during bulk email and phone reveal, which are actively reported to prevent exceeding your Apollo data quota.

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