icp-lookalike-expansion

Installation
SKILL.md

Use this when a few leads converted and you need more like them. It produces a deduplicated target list built on a similarity definition you chose, not one a vendor's feed chose for you.

The play

  1. Read the seed properly. Pull the seed's full record and extract two things: current title and current employer. That pair is the similarity signature. Everything downstream depends on it being right, so read the actual current role rather than the headline, which is often aspirational or stale.

  2. Decide what "similar" means. There are two different searches and they answer different questions:

    • Peers inside the same company — title plus employer. Use when you are mapping a buying committee or expanding within a won account.
    • The same role across the market — title only, optionally narrowed by geography. Use when you are building a net-new list. Drop the employer filter or you will get nothing.
  3. Search on short titles. Pass the core role, not the decorated headline. "Chief executive officer" works; "CEO & Founder | Investor | Speaker" returns zero. Most title matching is loose, so a shorter string casts the right net.

  4. Branch deliberately if you need depth. Depth 1 searches off the seed alone. Depth 2 takes each discovered profile, reads its role and employer, and searches again. Depth 2 is dozens of lookups; depth 3 is hundreds. Cap how many profiles you branch on (top 10 is usually enough) and confirm the spend before going past depth 2.

  5. Deduplicate by handle and drop the seed. The same person surfaces under many searches, and most search endpoints return the seed itself. Keep a seen-set across the whole run.

  6. Return a clean list, not the recursion tree: handle, name, headline, location, and which seed it came from.

What good looks like

Installs
1
GitHub Stars
165
First Seen
Sep 21, 2026
icp-lookalike-expansion — swan-gtm/gtm-skills