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buyer-prospector

Filter nationwide buyer data by county and state into an Excel workbook with decision-maker fields.

1|Updated Apr 22, 2026
Search Tags:#data-cleaning#county#investors#buyers#skip tracing#real estate data
One-click install
npx skills add https://github.com/seanpjones-collab/SiftStack --skill buyer-prospector
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: buyer-prospector
Source: https://github.com/seanpjones-collab/SiftStack/tree/main/.claude/skills/buyer-prospector
Command: npx skills add https://github.com/seanpjones-collab/SiftStack --skill buyer-prospector

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, openpyxl, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Pulls active real estate buyers data for a specified US county from a nationwide dataset, filters by county/state, and identifies decision-makers behind entities to enable targeted follow-up.

Core Features & Use Cases

  • Filters nationwide buyer data by county/state and categorizes entities (LLC, TRUST, CORPORATION, ESTATE, INDIVIDUAL, etc.).
  • Generates a multi-tab Excel workbook with All Records, Found, and Not Found sections containing decision-maker fields and addresses.
  • Provides a structured workflow to research decision-makers for high-priority entities and deliver a ready-to-skip-trace dataset.

Quick Start

Provide a county and state to generate a tailored buyers list.

Frequently Asked Questions about buyer-prospector

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I filter real estate buyers data by county and state?▼

To filter real estate buyers data by county and state, the Skill applies geographic filters to a nationwide dataset and outputs a structured Excel workbook with categorized buyer records and decision-maker fields.

Can I categorize real estate buyer entities like LLCs and trusts in Excel?▼

Yes, you can categorize real estate buyer entities by applying a Python script to classify LLC, TRUST, CORPORATION, and INDIVIDUAL records, generating a multi-tab Excel workbook for structured analysis.

How do I prepare a skip tracing list for real estate decision-makers?▼

You prepare a skip tracing list by filtering buyer data to populate decision-maker research columns, separating records into Found and Not Found Excel tabs ready for targeted follow-up.

Do I need pandas to build county buyers lists from nationwide data?▼

Yes, you need pandas along with openpyxl dependencies to run the Python script that filters nationwide data by county and outputs the structured Excel workbook with buyer records.

What is the best way to structure a real estate buyers dataset for follow-up?▼

The best way to structure a real estate buyers dataset is to use a Python script to categorize entities and output an Excel workbook with All Records, Found, and Not Found tabs containing research-ready decision-maker columns.

How does the decision-maker research workflow handle buyers that are not found?▼

The decision-maker research workflow handles not found buyers by isolating them in a dedicated Not Found tab within the Excel workbook, ensuring high-priority entities remain separated for further skip tracing investigation.

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