lookalike-prospect

What this skill does

# Lookalike Prospect

Expand an ICP from a reference set of known-good companies or contacts. Requires a minimum of 5 references — the lookalike model degrades significantly below this threshold.

## Step 1 — Validate Input Count

Count the number of reference companies or contacts provided.

**If fewer than 5 are provided**, stop and explain before doing anything else:

> "Lusha's lookalike model needs at least 5 reference [companies/contacts] to return quality results — fewer than that produces unreliable matches. You've provided [N]. Can you add [5−N] more?"

Do not proceed until the user has provided at least 5 references.

**If 5 or more are provided**, confirm the reference set with the user:

> "Running lookalike search using these [N] [companies/contacts] as the reference set: [list]. Shall I proceed?"

## Step 2 — Determine Mode

Based on the user's input, determine whether this is a **company lookalike** or **contact lookalike** search:

- References are company names or domains → **company mode**
- References are person names, emails, or titles → **contact mode**
- Mixed input → ask the user to clarify

## Step 3 — Resolve Reference IDs

**Company mode:** Use `mcp__lusha__companies_search` to resolve each reference company to a Lusha company ID. If a company can't be resolved, flag it and ask the user to confirm a substitute or proceed without it (only if at least 5 remain).

**Contact mode:** Use `mcp__lusha__contacts_search` to resolve each reference person to a Lusha contact ID. Apply the same fallback logic if a contact can't be resolved.

## Step 4 — Run Lookalike Search

**Company mode:** Use `mcp__lusha__lookalike_companies` with the resolved company IDs. Request up to 25 results.

**Contact mode:** Use `mcp__lusha__lookalike_contacts` with the resolved contact IDs. Request up to 25 results.

## Step 5 — Find Decision Makers (Company Mode Only)

For each lookalike company, use `mcp__lusha__prospecting_contact_search` to find the right contacts. If the user hasn't specified a target role, ask: *"What title or seniority are you targeting at these companies?"*

Resolve title/seniority filters via `mcp__lusha__prospecting_contact_filters` before searching.

## Step 6 — Enrich and Reveal Phones

Use `mcp__lusha__prospecting_contact_enrich` on the top results to reveal direct and mobile numbers. State the credit count before enriching batches larger than 10.

## Step 7 — Present Results

### Reference Set Used
List the [N] references that were used. Flag any that could not be resolved.

### Lookalike Results

**Company mode:**

| # | Company | Industry | Size | Revenue | Location | Contact Name | Title | Direct Phone | Mobile | Email |
|---|---------|----------|------|---------|----------|-------------|-------|-------------|--------|-------|

**Contact mode:**

| # | Name | Title | Company | Industry | Direct Phone | Mobile | Email |
|---|------|-------|---------|----------|-------------|--------|-------|

- Phone columns always appear before email — never reversed
- Mark missing phones with `—`

### Summary
- Lookalike [companies/contacts] found: X
- Decision makers enriched: Y
- Verified phones revealed: Z

## Step 8 — Offer Next Actions

1. **Narrow results** — apply additional filters (industry, geography, company size) to the lookalike list
2. **Cross with signals** — run `signal-prospect` on this lookalike list to surface which ones are showing buying signals right now
3. **Expand the reference set** — add more references to improve match quality
4. **Export** — format as CSV