Agent skill · marketing growth · borghei
lead-researcher
Qualify and prioritize sales leads against an ICP, score lead lists, and draft personalized outreach hooks. Use when building a target account list, qualifying inbound leads, prepping for outreach, or scoring prospects.
Why this skill is useful
Adds a Python script for lead qualification that automates scoring against an Ideal Customer Profile, which the AI wouldn't reliably generate on its own.
What it needs
Requires python installed locally. About 4k tokens when loaded. Last updated 2026-07-21. 462 stars on the source repository.
What this skill does
Lead Researcher Score and qualify sales leads against an Ideal Customer Profile (ICP) definition, then draft outreach hooks tied to specific ICP signals. --- Table of Contents Keywords Quick Start Core Workflows Tools Reference Guides Templates Best Practices --- Keywords lead, leads, prospect, prospecting, sales, outbound, ICP, ideal customer profile, qualify, qualification, scoring, account list, target account, outreach, cold email, BDR, SDR, account executive --- Clarify First Before scoring leads, confirm these inputs. If any is unknown or vague, ASK — do not assume: [ ] ICP definition — the must-have / nice-to-have / disqualifier attributes; this IS the scoring model [ ] Lead list columns — company, industry, size, country at minimum; missing fields mean no usable score [ ] GTM motion — PLG vs sales-led vs channel changes which signals weight highest and the outreach-hook framing Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact. --- Quick Start Score a Lead List in 10 Minutes 1. Define your ICP in icp.json using the schema in assets/icpschema.json 2. Save your lead list as a CSV with columns: company,industry,size,country,website,signals 3. Run the qualifier: 4. Review the ranked output — top 20% is your A-tier outreach list --- Core Workflows Workflow 1: ICP-Based Lead Scoring Goal: Rank a list of candidate accounts so the top of the list reflects the best fit, not the most recent import. Steps: 1. Build your ICP in icp.json — see assets/icpschema.json for the full schema 2. Capture leads in a CSV with at minimum: company,industry,size,country 3. Run: python scripts/leadqualifier.py icp.json leads.csv 4. Sort the result by score (highest first); the top 20% is your A-tier 5. Discard everything below the disqualification threshold rather than mass-emailing Expected Output: Ranked list with score, tier (A/B/C/disqualified), and reason per lead. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills borghei/lead-researcher