Lead Research Assistant
Research and qualify potential leads for a given product or service. Produce a scored, prioritized list of target companies with decision-maker contacts and personalized outreach strategies.
Workflow
1. Understand the offering
- If inside a code repository, read the README and key source files to infer the product.
- Clarify: what problem does it solve, for whom, and what is the core value proposition?
- Confirm the user's target market constraints (industry, geography, company size, budget range).
2. Define the Ideal Customer Profile (ICP)
Produce a short ICP summary covering:
| Dimension |
Detail |
| Industry / sector |
e.g., fintech, healthtech |
| Company size |
employee count or revenue band |
| Geography |
target regions |
| Pain points |
problems the offering addresses |
| Tech signals |
relevant stack, tools, or platforms |
| Budget indicators |
funding stage, revenue tier |
Checkpoint: confirm the ICP with the user before researching.
3. Research and identify leads
Use web search to find companies matching the ICP. For each candidate:
- Verify the company is active (recent news, job postings, social presence).
- Look for need signals: relevant job listings, tech stack mentions, recent funding, expansion announcements.
- Identify the decision-maker role (e.g., VP Engineering, Head of Security) and locate their LinkedIn profile when possible.
- Cross-check at least two sources before including a lead.
Checkpoint: if fewer than half the requested leads pass verification, widen search criteria and inform the user.
4. Score and prioritize
Assign each lead a fit score (1-10) based on:
- ICP alignment (industry, size, geography)
- Strength of need signals
- Budget likelihood
- Competitive gap (no incumbent solution visible)
- Timing (recent trigger events)
Sort leads by score descending.
5. Produce the output
Use this template for each lead:
## [Company Name]
**Website:** [URL]
**Score:** [X/10] - [one-line rationale]
**Industry:** [sector] | **Size:** [employees/revenue] | **Location:** [HQ]
**Why they fit:** [2-3 sentences citing specific evidence]
**Decision-maker:** [Title] - [Name if found] | [LinkedIn URL if available]
**Outreach angle:**
- Reference: [specific company event, pain point, or public statement]
- Value hook: [how the offering solves their specific problem]
- Opener: [one concrete conversation starter]
Prefix the list with a summary table:
# Lead Research Results
| # | Company | Score | Industry | Decision-maker |
|---|---------|-------|----------|----------------|
| 1 | ... | 9/10 | ... | ... |
6. Offer next steps
After presenting results:
- Offer to export as CSV for CRM import.
- Offer to draft personalized outreach emails for top-scored leads.
- Suggest deeper research on any lead the user flags.
1---2name: lead-research-assistant3description: >-4 Researches and qualifies sales leads by defining an ideal customer profile,5 searching for matching companies, scoring fit, and generating personalized6 outreach strategies with decision-maker contacts. Use when asked to find leads,7 prospect companies, identify potential customers, do lead generation, build a8 pipeline, research target accounts, find outreach targets, or identify ICP matches.9---1011# Lead Research Assistant1213Research and qualify potential leads for a given product or service. Produce a scored, prioritized list of target companies with decision-maker contacts and personalized outreach strategies.1415## Workflow1617### 1. Understand the offering1819- If inside a code repository, read the README and key source files to infer the product.20- Clarify: what problem does it solve, for whom, and what is the core value proposition?21- Confirm the user's target market constraints (industry, geography, company size, budget range).2223### 2. Define the Ideal Customer Profile (ICP)2425Produce a short ICP summary covering:2627| Dimension | Detail |28|-----------|--------|29| Industry / sector | e.g., fintech, healthtech |30| Company size | employee count or revenue band |31| Geography | target regions |32| Pain points | problems the offering addresses |33| Tech signals | relevant stack, tools, or platforms |34| Budget indicators | funding stage, revenue tier |3536**Checkpoint:** confirm the ICP with the user before researching.3738### 3. Research and identify leads3940Use web search to find companies matching the ICP. For each candidate:4142- Verify the company is active (recent news, job postings, social presence).43- Look for need signals: relevant job listings, tech stack mentions, recent funding, expansion announcements.44- Identify the decision-maker role (e.g., VP Engineering, Head of Security) and locate their LinkedIn profile when possible.45- Cross-check at least two sources before including a lead.4647**Checkpoint:** if fewer than half the requested leads pass verification, widen search criteria and inform the user.4849### 4. Score and prioritize5051Assign each lead a fit score (1-10) based on:5253- ICP alignment (industry, size, geography)54- Strength of need signals55- Budget likelihood56- Competitive gap (no incumbent solution visible)57- Timing (recent trigger events)5859Sort leads by score descending.6061### 5. Produce the output6263Use this template for each lead:6465```markdown66## [Company Name]6768**Website:** [URL]69**Score:** [X/10] - [one-line rationale]70**Industry:** [sector] | **Size:** [employees/revenue] | **Location:** [HQ]7172**Why they fit:** [2-3 sentences citing specific evidence]7374**Decision-maker:** [Title] - [Name if found] | [LinkedIn URL if available]7576**Outreach angle:**77- Reference: [specific company event, pain point, or public statement]78- Value hook: [how the offering solves their specific problem]79- Opener: [one concrete conversation starter]80```8182Prefix the list with a summary table:8384```markdown85# Lead Research Results8687| # | Company | Score | Industry | Decision-maker |88|---|---------|-------|----------|----------------|89| 1 | ... | 9/10 | ... | ... |90```9192### 6. Offer next steps9394After presenting results:9596- Offer to export as CSV for CRM import.97- Offer to draft personalized outreach emails for top-scored leads.98- Suggest deeper research on any lead the user flags.
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