Research and qualify business leads against your ICP
Scanned 5/27/2026
Install via CLI
openskills install cognyai/claude-code-marketing-skills---
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 │
└──────────────┴──────────────────┴──────────┴───────────────┘
```
No comments yet. Be the first to comment!
End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches.
Orchestrate multi-phase deep research with web search, memory retrieval, pattern matching, and synthesis into structured findings
Persistent memory systems for LLM conversations including short-term, long-term, and entity-based memory Use when: conversation memory, remember, memory persistence, long-term memory, chat history.
CodeTour `.tour`ファイルを作成 — ペルソナターゲット、ステップバイステップウォークスルー(実際のファイルとラインアンカー付き)。オンボーディングツアー、アーキテクチャウォークスルー、PRツアー、RCAツアー、構造化「これがどのように機能するかを説明」リクエストに使用。
showコマンド、コンフィグ階層、ワイルドカードマスク、ACL配置、インターフェースハイジーン、安全な変更ウィンドウ検証のためのCisco IOSおよびIOS-XEレビューパターン。