TL;DR

X-ray search is a Boolean sourcing technique that uses search engines -- primarily Google -- to search within a specific website using the site: operator. It allows recruiters to find candidate profiles on LinkedIn, GitHub, and other platforms without being constrained by those platforms' own search tools.

How It Works

Google's site: operator restricts search results to a single domain, turning the world's most powerful search engine into a scalpel for sourcing. A basic X-ray search on LinkedIn looks like this:

site:linkedin.com/in "software engineer" "[machine learning](/glossary/machine-learning)" London

This instructs Google to return only pages within the linkedin.com/in subdirectory (individual profiles, not company pages) that contain the terms "software engineer", "machine learning", and "London". The results are LinkedIn profiles indexed by Google -- including profiles that are partially visible to non-connected users.

The technique extends to any indexable platform. GitHub profiles can be searched with site:github.com to find developers by language, project type, or location data they've included in their profiles. Stack Overflow, personal portfolio sites, conference speaker directories, academic pages, and professional association directories are all fair game.

The power is in combining operators. Quotation marks for exact phrases, the minus sign to exclude terms (-jobs -hiring -recruiter), the OR operator for synonyms ("product manager" OR "product owner"), and location-specific terms all stack to narrow results to highly relevant profiles.

Why It Matters for Recruitment

LinkedIn [Recruiter](/glossary/recruiter) is expensive and its search algorithm has its own biases, keyword weighting, and subscription-tier restrictions. X-ray search bypasses all of that. It searches what Google has indexed from the public-facing version of profiles, which includes information that LinkedIn's own search might de-prioritise or exclude.

For agency recruiters who don't have LinkedIn Recruiter licences, X-ray search is often the primary sourcing tool for LinkedIn profiles. For those who do have Recruiter, X-ray search complements it -- surfacing profiles that LinkedIn's algorithm would not have surfaced, or allowing more precise keyword targeting than the Recruiter interface supports.

GitHub X-ray searches are particularly useful for technical roles. A developer's public repositories, commit history, and profile readme contain more signal about their actual skills than a LinkedIn profile that summarises those skills in buzzword-heavy bullet points. A search like site:github.com "Python" "machine learning" "open source" combined with location terms and follower count proxies finds active practitioners, not just people who listed the skill on a profile.

The limitation is coverage. Google only indexes public content. Profiles set to private, content behind login walls not accessible to Google's crawler, and content that hasn't been recently re-indexed won't appear. X-ray search is a complement to direct sourcing, not a complete replacement.

In Practice

A recruiter is sourcing for a Rust developer role in Berlin. LinkedIn Recruiter returns 12 results for "Rust" in Berlin with the right experience level. X-ray search on GitHub returns 34 profiles of developers with public Rust repositories who list Berlin in their profile.

Of the 34, several have no LinkedIn presence at all. One has a popular open-source Rust library with 400 GitHub stars -- exactly the kind of candidate who isn't actively applying and won't appear in standard searches. The recruiter reaches out via GitHub's contact options and secures a response within 48 hours.

Key Facts