/lead-qualification
Research and qualify business leads against your ICP
$ npx -y skills add cognyai/claude-code-marketing-skills --skill lead-qualification --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/lead-qualification
Context preview
The summary Claude sees to decide when to auto-load this skill.
Research and qualify business leads against your ICP
SKILL.md
lead-qualification.SKILL.mdname: lead-qualification
description: Research and qualify business leads against your ICP
version: "1.0.0"
author: Cogny AI
platforms: []
user-invocable: true
argument-hint: "<name> <email or company>"
allowed-tools:
- WebFetch
- WebSearch
- Bash
- Read
- Write
Lead Qualification
Research a lead or list of leads to determine ICP fit, company details, and deal potential.
Usage
`/lead-qualification "John Smith john@company.com"` — qualify a single lead `/lead-qualification` — then paste a list of leads
Steps
1. Parse the lead(s)
Extract name, email, and company from input. If email domain is personal (gmail, hotmail, outlook, yahoo, live), flag it — personal emails are a lower-quality B2B signal.
2. Research each lead
For each lead, WebSearch for:
- Full name + company → LinkedIn profile, role, seniority
- Company domain → website, size, industry
- Company + "marketing" or "advertising" → whether they do paid media
3. Assess company fit
WebFetch the company website if found:
- What do they sell?
- How big are they? (team page, about page, funding)
- Do they run ads? (check for tracking pixels, ad landing pages)
- What's their likely marketing budget?
4. Score each lead
Lead: [Name] ([email])
Company: [Company] — [what they do]
Role: [Title/seniority if found]
ICP Fit: HIGH / MEDIUM / LOW / NONE
Signals:
+ [Positive signal, e.g., "Runs Google Ads"]
+ [Another positive]
- [Negative signal, e.g., "Personal email"]
- [Another negative]
Estimated deal value: [based on company size]
Next step: [specific recommendation]
5. Summary table for multiple leads
┌──────────────┬──────────────────┬──────────┬───────────────┐
│ Name │ Company │ ICP Fit │ Next Step │
├──────────────┼──────────────────┼──────────┼───────────────┤
│ [Lead 1] │ [Company] │ HIGH │ Send proposal │
│ [Lead 2] │ [Unknown] │ LOW │ Disqualify │
└──────────────┴──────────────────┴──────────┴───────────────┘
Read more
name: lead-qualification description: Research and qualify business leads against your ICP version: "1.0.0" author: Cogny AI platforms: [] user-invocable: true argument-hint: "<name> <email or company>" allowed-tools: - WebFetch - WebSearch - Bash - Read - Write
Lead Qualification
Research a lead or list of leads to determine ICP fit, company details, and deal potential.
Usage
`/lead-qualification "John Smith john@company.com"` — qualify a single lead `/lead-qualification` — then paste a list of leads
Steps
1. Parse the lead(s)
Extract name, email, and company from input. If email domain is personal (gmail, hotmail, outlook, yahoo, live), flag it — personal emails are a lower-quality B2B signal.
2. Research each lead
For each lead, WebSearch for:
- Full name + company → LinkedIn profile, role, seniority
- Company domain → website, size, industry
- Company + "marketing" or "advertising" → whether they do paid media
3. Assess company fit
WebFetch the company website if found:
- What do they sell?
- How big are they? (team page, about page, funding)
- Do they run ads? (check for tracking pixels, ad landing pages)
- What's their likely marketing budget?
4. Score each lead
Lead: [Name] ([email]) Company: [Company] — [what they do] Role: [Title/seniority if found] ICP Fit: HIGH / MEDIUM / LOW / NONE Signals: + [Positive signal, e.g., "Runs Google Ads"] + [Another positive] - [Negative signal, e.g., "Personal email"] - [Another negative] Estimated deal value: [based on company size] Next step: [specific recommendation]
5. Summary table for multiple leads
┌──────────────┬──────────────────┬──────────┬───────────────┐ │ Name │ Company │ ICP Fit │ Next Step │ ├──────────────┼──────────────────┼──────────┼───────────────┤ │ [Lead 1] │ [Company] │ HIGH │ Send proposal │ │ [Lead 2] │ [Unknown] │ LOW │ Disqualify │ └──────────────┴──────────────────┴──────────┴───────────────┘
AI marketing skills for Claude Code, Cursor, Windsurf, and other AI coding tools. Audit SEO, analyze ads, research competitors, qualify leads — all from your terminal. Free skills need no account. Premium skills connect your real data for $9/mo.
Repo: cognyai/claude-code-marketing-skills
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