people-sourcer

Source named people from online platforms into a structured xlsx spreadsheet.

16|2|Updated Feb 12, 2026
One-click install
npx skills add https://github.com/thtskaran/claude-skills --skill people-sourcer
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: people-sourcer
Source: https://github.com/thtskaran/claude-skills/tree/main/people-sourcer
Command: npx skills add https://github.com/thtskaran/claude-skills --skill people-sourcer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you source specific people from the right online platforms and compile them into a spreadsheet with actionable, per-person context so outreach is relevant instead of spammy.

Core Features & Use Cases

  • Signal-first people sourcing: Collects named individuals using iterative discovery and scraping across platforms like LinkedIn, Reddit, X, GitHub, and more, anchored to the user’s persona and signals.
  • Enrichment and contact discovery: Builds a structured candidate dataset with verified profile details and preferred contact channel options based on publicly available information.
  • Per-row personalization (worldbuilder lens): Produces tailored “Why They Fit” and “Outreach Angle” fields grounded in each candidate’s actual scraped signal (post/talk/repo/milestone).
  • Spreadsheet output for outreach: Generates a multi-sheet Excel workbook (People, Sources, Outreach Playbook) suitable for Google Sheets and real follow-up workflows.

Quick Start

Use the people-sourcer skill to create a Google-Sheets-compatible xlsx by asking: find 50 senior backend engineers in the EU who post about Rust, and output a people spreadsheet with per-person outreach angles.

Frequently Asked Questions about people-sourcer

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

FAQPage Schema
How do I generate a lead generation spreadsheet with personalized outreach angles?

To generate a lead generation spreadsheet, this Skill iteratively discovers and scrapes named individuals across platforms, enriches their profile data, and outputs a multi-sheet xlsx workbook containing per-row personalized outreach context. It compiles verified contact details and tailored outreach angles into a structured file ready for immediate follow-up workflows.

What is the best way to source candidates from platforms like LinkedIn and GitHub into a spreadsheet?

The best way to source candidates into a spreadsheet is using signal-first iterative discovery and scraping across platforms like LinkedIn, GitHub, Reddit, and X. This approach cross-references publicly available profile data, stitches the verified information together, and exports a structured contact list with per-person context for recruiting or sales prospecting.

Can I use web scraping to build prospect lists with per-person personalization fields?

Yes, you can use web scraping to build prospect lists that include per-person personalization fields. The Skill anchors outreach context to each candidate's actual scraped signals, such as specific posts, talks, or repositories, generating tailored 'Why They Fit' and 'Outreach Angle' columns directly within the exported xlsx file.

Does the people sourcing output work with Google Sheets for sales prospecting?

Yes, the people sourcing output works with Google Sheets for sales prospecting because the Skill generates a Google-Sheets-compatible xlsx workbook. This file contains separate sheets for the compiled people list, their sources, and an outreach playbook, ensuring seamless import and real-time collaboration during follow-up campaigns.

How do I find and enrich research participants from online platforms?

You can find and enrich research participants by defining your target persona and signals, which triggers iterative discovery across relevant online platforms. The Skill then performs cross-platform stitching to verify profile details and compiles the enriched participant data into an actionable spreadsheet complete with preferred contact channels.

What limitations exist when scraping profiles for candidate enrichment?

A key limitation when scraping profiles for candidate enrichment is reliance on publicly available information across platforms like LinkedIn, Reddit, and X. The process depends on accessible signal data such as posts or repositories, and constraints may arise if specific profile data or contact channels are hidden behind platform privacy settings.