Create a Boolean sourcing search plan for the role below. I need search strings that find people with evidence of the required work, not proxies for age, race, gender, disability, nationality, family status, or other protected characteristics. Role requirements: [JOB REQUIREMENTS] Must-have and acceptable substitute skills: [SKILL CRITERIA] Target location, work authorization rules, and work arrangement: [LOCATION AND ELIGIBILITY] Approved sourcing policy and excluded terms: [COMPANY SOURCING POLICY] First, separate the requirements into: essential skills, adjacent or transferable skills, seniority evidence, industry context, and non-negotiable eligibility. Treat titles as imperfect signals; include realistic title variants and skill-based alternatives. Do not use school names, graduation years, gendered terms, demographic groups, or arbitrary prestige filters unless an input explicitly establishes a lawful business need.
Produce these sections: 1. A requirement map showing the exact concepts and synonyms you will search. 2. Three ready-to-paste Boolean strings: LinkedIn Recruiter, Google X-ray, and a generic résumé database. Keep each under the platform’s likely query limits where possible. 3. A narrower “high-confidence” string and a broader “adjacent talent” string for each platform. 4. A table explaining every AND, OR, NOT, quotation mark, and site filter in plain language. 5. A short validation plan: sample 20 results, note false positives and missed qualified profiles, then name the terms to add or remove. Do not claim that you ran the search or found candidates. Flag any eligibility requirement that may need legal or HR review. Before answering, check that every exclusion is job-related and that the broad version can surface qualified people with nontraditional titles or backgrounds. Ask up to 3 clarifying questions only if a required input is missing.
Fill in
| Placeholder | What to enter | Example |
|---|---|---|
| [JOB REQUIREMENTS] | Paste the job description or a concise list of the role’s duties, required experience, and outcomes. | Senior data analyst; build retention dashboards, write SQL, partner with product managers, and present findings to executives; 4+ years preferred. |
| [SKILL CRITERIA] | List must-have skills, preferred skills, acceptable substitutes, and tools the person will use. | Must have SQL and dashboarding; Tableau or Looker accepted; Python preferred; product analytics or subscription-business experience is helpful. |
| [LOCATION AND ELIGIBILITY] | State the work location or remote arrangement and any verified, lawful work-eligibility requirement. | United States, remote; candidate must be authorized to work in the U.S. without current or future sponsorship. |
| [COMPANY SOURCING POLICY] | Paste approved sourcing rules, prohibited filters, diversity guidance, and any platform restrictions. | Use job-related criteria only. Do not filter by school, age, name, photo, graduation date, demographic group, or prior employer prestige. |
How to use
- Paste the role requirements and distinguish genuine requirements from preferences before generating the strings.
- Run the broad string first and inspect 20 to 30 profiles for relevant work evidence, not just title matches.
- Remove terms that create repeated false positives, then test the high-confidence string against known strong profiles.
- Send this follow-up: “Revise the LinkedIn string using these five false positives and these three qualified profiles it missed: [EXAMPLES].”
Variations
Passive talent search
Use this when you are sourcing people who may not be actively applying.
Build a passive-candidate Boolean search for [ROLE] in [LOCATION]. Required work evidence is [MUST-HAVES]; adjacent backgrounds that count are [TRANSFERABLE BACKGROUNDS]. Create LinkedIn and Google X-ray strings with title variants, skill synonyms, and realistic portfolio or project terms. Do not use demographic, school, age, or prestige proxies. Return a broad and narrow string, a list of likely false positives, and three outreach-relevant profile signals. Flag any eligibility filter that needs HR review.
Technical talent search
Use this for a role where stack terminology and seniority signals matter.
Create Boolean strings for hiring a [TECHNICAL ROLE]. The production stack is [STACK], the critical responsibilities are [RESPONSIBILITIES], and acceptable alternative tools are [ALTERNATIVES]. Produce strings for LinkedIn Recruiter, GitHub Google X-ray, and a résumé database. Include title variants, open-source or portfolio evidence, and negative terms only where they remove a documented false positive. Explain the tradeoff of each restriction. Check that the search does not treat degree pedigree or employer brand as a substitute for capability.
Search audit
Use this after a search returns too few relevant profiles or too many irrelevant ones.
Audit this Boolean string: [CURRENT STRING]. The intended role is [ROLE], strong-result examples are [GOOD RESULTS], and recurring false positives are [FALSE POSITIVES]. Diagnose which clauses are over-restrictive, ambiguous, redundant, or missing synonyms. Return a revised broad string, revised narrow string, and a change log that says why each edit was made. Preserve only job-related filters and flag exclusions that could create unfair screening.
Tips
- Build searches around evidence of work performed, such as “cohort analysis” or “dbt,” rather than relying only on a target title.
- Keep a broad string and a narrow string; one query cannot serve both discovery and final shortlist-building.
- Test exclusions carefully because NOT operators often hide qualified people whose profiles mention an unrelated prior role.
- Record examples of false positives and false negatives so future recruiters can improve the shared search without adding subjective filters.
FAQ
Can AI search LinkedIn and return candidates for me?
This prompt creates query logic and a testing plan. Use it in your approved sourcing tools and assess profiles under your normal hiring process.
Should I exclude candidates who lack a degree?
Only if a degree is a documented, job-related requirement. Skills, work samples, certifications, and comparable experience often provide better evidence.