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onewave-ai avatar

Linkedin Sales Navigator Alt

onewave-ai/claude-skills
429 installs244 stars
Summary

This outputs highly structured prospect lists by scraping publicly available LinkedIn data and enriching it with business intelligence signals. You define your ICP (industry, company size, geography, tech stack), specify decision maker personas, and get back formatted lists grouped by company, job title, or priority level. It flags hot leads like recent job changes and includes personalization hooks pulled from profiles and company news. The formatting is aggressive, bordering on boilerplate heavy, but if you're doing outbound at scale and need consistent lead data without paying for Sales Navigator, it systematically organizes what you'd otherwise compile manually. Just know you're still doing the email verification and actual outreach yourself.

Install to Claude Code

npx -y skills add onewave-ai/claude-skills --skill linkedin-sales-navigator-alt --agent claude-code

Installs into .claude/skills of the current project.

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Files
SKILL.mdView on GitHub

LinkedIn Sales Navigator Alternative

Find and qualify prospects on LinkedIn without expensive subscriptions, using only publicly available information.

Contents

  • references/output-template.md — full prospect-list Markdown structure and section layout
  • references/campaigns.md — segmented campaign playbooks (new-in-role, account-based, event follow-up)
  • references/tools-and-export.md — contact-finding methods, tool stack, CSV/CRM export formats
  • references/examples.md — trigger phrases, example request, best practices

Compliance

Work only with publicly available information and respect LinkedIn's Terms of Service. Encourage official LinkedIn tools where appropriate. Aggregate public data for legitimate business development only.

Workflow

  1. Define the Ideal Customer Profile (ICP). Capture industry/sector, company size (employees, revenue), geography, tech stack, and funding stage.

  2. Identify decision-maker personas. Map the primary buyer, influencers, the economic buyer (budget holder), and the technical buyer (evaluation team).

  3. Build the search strategy. Set job-title patterns, company criteria, location filters, seniority level, and description keywords. Choose a list-building approach: account-based, role-based, industry-based, event-based (job changes, funding rounds), or geography-based.

  4. Collect and enrich data (public info only). Compile name, title, company, size, location, industry, public activity, and shared connections. Verify company details, find contact information, add personalization context, and score lead quality. See references/tools-and-export.md for discovery and verification methods.

  5. Prioritize and segment. Tag hot leads (recent job changes), warm leads (shared connections), and cold leads (no prior contact). Group by account for campaigns.

  6. Deliver the prospect list. Format the output per references/output-template.md, attach relevant campaign playbooks from references/campaigns.md, and provide export-ready data per references/tools-and-export.md.

Deliver a targeted, researched set of qualified prospects with personalization context — not just a list of names. See references/examples.md for trigger phrases and best practices.

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Categories
DevOps & CI/CDProductivity & PlanningSales & Marketing
First SeenJun 3, 2026
View on GitHub

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