This is a structured research assistant that helps you find and organize contact information for sales prospecting or outreach. It doesn't actually scrape data or call APIs. Instead, it gives you targeted search queries for LinkedIn, Google, and company websites, suggests likely email patterns based on what you find, and provides templates to organize everything consistently. The real value is in how it breaks down the hunting process into systematic steps and helps you spot email patterns across a company. Just be aware you're still doing the manual legwork, it's more like having a methodology than having automation. Good for building prospect lists when you don't have access to paid tools like ZoomInfo or Apollo.
npx -y skills add onewave-ai/claude-skills --skill contact-hunter --agent claude-codeInstalls into .claude/skills of the current project.
Find and enrich publicly available contact information from multiple sources with full source attribution.
This skill guides the search process and organizes results. It does not directly access paid APIs; it produces structured queries, suggests where to look, then validates and formats what is found.
references/search-queries.md — per-target search briefs and reusable query patternsreferences/output-templates.md — data collection template, contact card, bulk CSV, email-pattern report, export formatsreferences/compliance.md — allowed/not-allowed rules, best practices, verification stepsIdentify the search type: person, company, role, email verification, or bulk enrichment.
Gather search parameters: name, company, job title, location, industry, LinkedIn URL, email domain, and any other identifiers.
Select sources to check: LinkedIn, company website (About/Team/Contact/Leadership), GitHub (developers), Twitter/X, professional directories, public databases, and any paid tools the user has access to (ZoomInfo, Apollo.io, Hunter.io, RocketReach).
Build the search plan using the query patterns in references/search-queries.md. Produce a per-target brief with LinkedIn, Google, company-website, email-pattern, and GitHub queries.
Detect the company email pattern from confirmed addresses, then derive candidate emails. See the email-pattern report in references/output-templates.md.
Collect and verify results. Cross-reference multiple sources and run the verification steps in references/compliance.md before recording any field.
Format output using the templates in references/output-templates.md: data collection template, individual contact card, or bulk CSV. Export as CSV, JSON, vCard, or CRM-specific CSV (Salesforce, HubSpot) as requested.
For enrichment of existing contacts, refresh: current job title, company changes, updated contact info, social profiles, company information, reporting structure, and recent activity.
Ensure every contact record includes all available fields, cites its sources, carries a confidence/verification level and freshness date, follows data-privacy law, is formatted consistently, notes contact preferences, provides role context (tenure, team), flags uncertainties, and suggests verification steps. Operate only within the rules in references/compliance.md.
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