Create Boolean searches for a recruiting assignment using only job-related, lawful criteria. I need searches that are usable in the named sourcing platform and consistent with our hiring policy. Role and must-have requirements: [ROLE REQUIREMENTS] Preferred but nonessential qualifications: [PREFERRED QUALIFICATIONS] Location, work authorization, and work arrangement rules: [LOCATION RULES] Target platform(s): [SOURCING PLATFORMS] Company policy or exclusions: [HIRING POLICY] Start by separating requirements into must-have, preferred, and evidence signals. Translate concepts into realistic title, skill, tool, industry, and seniority synonyms; do not treat an adjacent title as equivalent unless you label it as a broader-recall option. Avoid protected characteristics and proxies, including age, graduation year, names, gendered terms, ethnicity, religion, disability, family status, and schools used as a status filter. Produce: 1. One balanced-recall Boolean string for each platform, using its actual syntax and length limits where known. 2. One high-precision version and one broad-recall version, with the exact terms changed and why. 3. A term map with required concepts, accepted synonyms, deliberate exclusions, and likely false positives. 4. A short screening note distinguishing objective job requirements from preferences. 5. A 5-candidate calibration plan: what to inspect in results and how to revise terms without drifting from the agreed criteria. Use parentheses and OR groups correctly. Keep the role’s essential skills connected with AND; do not pile every preference into the main string. Do not claim a platform supports an operator unless stated in the input; flag unknown syntax instead. Ask up to 3 clarifying questions only if a required input is missing. Before answering, self-check for protected-class proxies and for Boolean logic that would accidentally exclude common valid titles or include an unrelated occupation.
Fill in
| Placeholder | What to enter | Example |
|---|---|---|
| [ROLE REQUIREMENTS] | List the role title and the nonnegotiable job-related skills, experience, and responsibilities. | Senior data analyst; 4+ years analyzing product data, advanced SQL, Tableau or Looker, and stakeholder reporting. |
| [PREFERRED QUALIFICATIONS] | List useful but optional skills, industries, certifications, or experience. | Experience with B2B SaaS, dbt, Amplitude, or experimentation analysis. |
| [LOCATION RULES] | State eligible locations, remote or hybrid policy, and any lawful work authorization requirements. | US remote; candidates must already be authorized to work in the US; no relocation requirement. |
| [SOURCING PLATFORMS] | Name the tools where you will run the search, such as LinkedIn Recruiter or an ATS. | LinkedIn Recruiter and Google X-ray search. |
| [HIRING POLICY] | Paste relevant equal-opportunity, qualification, or sourcing rules and exclusions. | Use only job-related criteria. Do not filter by school prestige, graduation year, name, or demographic information. |
How to use
- Replace the inputs with the approved job requirements and the exact platforms you use.
- Run the balanced string first and inspect the first 20 results for title fit and false positives.
- Check each exclusion with the hiring manager before adding it; preferences should not become hidden must-haves.
- Follow up with: “Here are 10 result titles and profiles. Revise recall without changing the approved requirements: [RESULTS].”
Variations
X-ray search
Use when searching public web profiles through Google or Bing.
Create a web X-ray search for public candidate profiles. Target role: [ROLE]. Required skills: [MUST HAVES]. Approved sites to search: [SITES]. Geography rule: [LOCATION]. Policy constraints: [POLICY]. Produce three query versions for Google, explain the site:, intitle:, and quoted phrases used, and list likely false positives. Keep terms job-related; do not use names, graduation years, demographic signals, or school prestige. Ask up to 3 questions only if needed. Self-check balanced parentheses and ensure every required skill is either queried or identified as something to verify manually.
Talent-pool mapping
Use when broadening the search beyond obvious job titles.
Map adjacent talent pools for this hiring search. Core role: [ROLE]. Essential capabilities: [ESSENTIAL CAPABILITIES]. Industries or environments that transfer well: [TRANSFERABLE BACKGROUNDS]. Non-negotiable constraints: [CONSTRAINTS]. Return a table of 6 to 10 adjacent titles, why each transfers, expected skill gaps, and an inclusive Boolean OR group for each cluster. Do not assume a title proves competence. Do not use demographic or prestige signals. Ask up to 3 questions only if a required input is missing. Check that every suggested pool can plausibly meet the essential capabilities without retraining beyond the role’s scope.
Search calibration
Use after an initial Boolean search returns weak or noisy results.
Improve this Boolean search based on actual results while preserving our approved criteria. Approved requirements: [APPROVED CRITERIA]. Current search: [CURRENT BOOLEAN]. Sample of relevant and irrelevant results: [RESULT SAMPLE]. Platform: [PLATFORM]. Diagnose which terms cause false positives, which valid titles are missing, and propose a revised search plus a change log. Keep preferences separate from must-haves and use only job-related language. Ask up to 3 questions only if required. Self-check that each change is tied to evidence from the result sample and that no new exclusion contradicts the approved criteria.
Tips
- Build the search around demonstrated capabilities and common job titles, then verify specifics in profiles rather than assuming a title guarantees skill.
- Use a high-precision string for urgent outreach and a broad-recall string for market mapping; one query rarely serves both jobs.
- Test synonyms on a small result set before adding them, because terms such as “analyst” or “engineer” often pull unrelated functions.
FAQ
Should every preferred skill go in the Boolean string?
Usually no. Adding every preference can cut out qualified people. Use preferences as a secondary filter or a separate high-precision version.
Can I search by university or graduation year?
Those filters can introduce unfair or policy-prohibited proxies. Use demonstrated job-related experience and skills instead.