Career
Boolean Search String Builder
Boolean Search String Builder turns career context into focused, credible application or development material with clear constraints and an explicit output.
The prompt
Boolean Search String Builder guides the model through a defined task while preserving the source prompt's useful structure and constraints. Use it when preparing for a job search, interview, or professional decision and you want a response that is easier to evaluate and act on.
text prompt
Build 5 advanced Boolean search strings I can use on LinkedIn Recruiter and Google X-ray to find candidates for this role: Job title: {{jobTitle}} Must-have skills: {{skill1Skill2Skill3}} Nice-to-have skills: {{skill4Skill5}} Target companies or industries: {{companiesIndustries}} Location: {{cityStateOrRemote}} Experience level: {{juniorMidSenior}} For each string, explain what it targets and suggest one variation that broadens the results by 20-30%. Format each string so I can copy-paste it directly into a search bar.
Tune the prompt, not the plumbing.
Every control comes from this prompt’s content schema. Changes stay in your browser and update instantly.
Customized prompt582 characters
Build 5 advanced Boolean search strings I can use on LinkedIn Recruiter and Google X-ray to find candidates for this role: Job title: a specific job title Must-have skills: a specific skill 1 skill 2 skill 3 Nice-to-have skills: a specific skill 4 skill 5 Target companies or industries: a specific companies industries Location: a specific city state or remote Experience level: a specific junior mid senior For each string, explain what it targets and suggest one variation that broadens the results by 20-30%. Format each string so I can copy-paste it directly into a search bar.
Useful structure, room to move.
Boolean Search String Builder guides the model through a defined task while preserving the source prompt's useful structure and constraints. Use it when preparing for a job search, interview, or professional decision and you want a response that is easier to evaluate and act on.
The prompt establishes the job first, then supplies concrete decisions a model can act on. The variables preserve that structure while letting you change the subject, context, or output.
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