linkedin-contact-reacher

Traverse LinkedIn networks via BFS/DFS to map contacts and generate email candidates.

3|Updated Feb 27, 2026

Search Tags:#automation #linkedin #output #contacts #bfs #dfs #email-generation

Ready to run

npx skills add https://github.com/yennanliu/linkedin-skill --skill linkedin-contact-reacher

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: linkedin-contact-reacher
Source: https://github.com/yennanliu/linkedin-skill/tree/main/skills/linkedin-contact-reacher
Command: npx skills add https://github.com/yennanliu/linkedin-skill --skill linkedin-contact-reacher

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automate the discovery and enrichment of LinkedIn contacts by traversing networks (BFS/DFS) from seeds or profiles, enabling targeted networking and referrals.

Core Features & Use Cases

BFS/DFS traversal with depth control to surface relevant contacts
Email candidate generation by inferring company domains and names
Optional outreach: send personalized connection requests with notes
Local output: JSON and CSV exports for downstream workflows
Use cases include finding referral candidates at target companies, networking from trusted connections, and building structured contact pipelines

Quick Start

Seed with search terms or profiles, run the discovery and enrichment workflow, and save the results to local JSON and CSV files.

Frequently Asked Questions about linkedin-contact-reacher

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

FAQPage Schema

How do I automate LinkedIn contact discovery and network traversal from a seed profile?▼

Automating LinkedIn contact discovery requires seeding the workflow with search terms or profiles and running BFS/DFS traversal to a set depth. This maps relevant contacts and enriches them with email candidates for networking.

How does BFS and DFS traversal work for finding LinkedIn referral candidates?▼

Finding LinkedIn referral candidates via BFS and DFS traversal maps networks outward from seed profiles. BFS explores broadly across immediate connections, while DFS goes deep into specific paths, bounded by configurable depth limits.

Do I need Playwright MCP tooling to run LinkedIn contact automation?▼

Yes, Playwright MCP tooling is required to run this LinkedIn contact automation. It provides the browser automation framework necessary to navigate profiles, traverse networks, and extract contact data with rate-limiting.

Can I generate and infer email addresses for LinkedIn contacts automatically?▼

Yes, generating email candidates automatically infers company domains and contact names from LinkedIn profiles. The enriched data is then exported to local JSON and CSV files for downstream networking workflows.

What is the best way to export enriched LinkedIn contacts to JSON and CSV?▼

Exporting enriched LinkedIn contacts is best done via a workflow that saves results directly to local JSON and CSV files. This requires local storage, ensuring structured contact pipelines are ready for downstream networking use.

How do I prevent getting blocked when automating LinkedIn connection requests?▼

Preventing blocks when automating LinkedIn connection requests requires using a workflow with built-in delays and rate-limiting. These safe automation practices ensure traversals and outreach actions stay within acceptable platform limits.