Generate powerful boolean search strings for sourcing candidates on LinkedIn, Google, GitHub, and job boards. Find the right talent faster with platform-specific queries.
Boolean search is a method of constructing search queries using logical operators—AND, OR, NOT—to find precisely the candidates you need. It is the core skill of any sourcer or recruiter who wants to go beyond basic keyword searches on LinkedIn or Google. The technique was originally developed for database querying, but it translates powerfully to candidate sourcing: instead of sifting through hundreds of irrelevant profiles, a well-built boolean string surfaces only the candidates who meet your specific criteria.
Boolean search is especially valuable for finding passive candidates—people who are not actively applying to jobs but who have the exact skills and experience you need. With X-ray search on Google, you can comb through LinkedIn profiles, GitHub repositories, and professional communities without hitting platform search limits or paying for premium tools. A skilled recruiter with strong boolean technique can outperform expensive sourcing software on most searches.
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Yes, the JuggleHire Boolean Search Generator is completely free. No sign-up required. Enter your job title, skills, and location to generate platform-specific boolean strings for LinkedIn, Google, and GitHub instantly.
Boolean search in recruiting is the use of logical operators (AND, OR, NOT) and special syntax to build precise search queries that find candidates matching specific criteria. Instead of a simple keyword search, boolean strings let you search for candidates who have one skill AND another, OR who have an alternative title, while NOT including irrelevant profiles.
Boolean search works by instructing the search engine to apply logical rules to results. AND narrows results (both terms must be present), OR broadens them (either term qualifies), and NOT excludes results containing a term. Parentheses group conditions, and quotes enforce exact phrase matching. For example: ("software engineer" OR "software developer") AND (Python OR Django) NOT "senior" finds mid-level Python developers.
LinkedIn's native search supports AND, OR, NOT, and quoted phrases—but does not support parentheses in the standard search bar (only in LinkedIn Recruiter). Google X-ray search (site:linkedin.com/in + boolean string) supports full boolean syntax including parentheses and is often more powerful for finding public profiles. GitHub search uses its own syntax (language:python location:london) which requires a different approach entirely.
The four most valuable operators for recruiters are: OR (to capture title variations like "VP Sales" OR "Head of Sales"), AND (to require multiple skills), NOT (to exclude irrelevant profiles like "NOT recruiter" when searching for sales roles), and quotes (to enforce exact phrases like "full stack"). Combining OR groups inside parentheses with AND between them is the most powerful pattern.
Passive candidates are not browsing job boards, so you must go to them. Google X-ray search (site:linkedin.com/in) combined with a strong boolean string finds LinkedIn profiles not surfaced by LinkedIn's own algorithm. Searching GitHub for active contributors in a technology, or searching professional community sites like dev.to or Stack Overflow, surfaces candidates who are engaged in their craft but not actively job hunting.
GitHub's people search supports filters like location, language, and followers. Use the search syntax: "location:london language:python followers:>50" to find active Python developers in London with an established profile. You can also use Google X-ray on GitHub: site:github.com "San Francisco" "machine learning" to surface relevant profiles from Google.
X-ray search is the technique of using Google (or another search engine) to search within a specific website using the "site:" operator. For example: site:linkedin.com/in "product manager" "fintech" "London" searches Google's index of LinkedIn profiles directly. This bypasses LinkedIn's search limits and often surfaces profiles that LinkedIn's own algorithm deprioritizes.