Create a copy-and-paste AI prompt library for my HR work. My organization and workforce context are [ORGANIZATION CONTEXT], the applicable locations and policies are [JURISDICTION AND POLICY CONTEXT], and the immediate people priorities are [HR PRIORITIES]. Our tone, approval process, and sensitive constraints are [COMMUNICATION AND PRIVACY RULES]. Ask up to 3 clarifying questions only if a required input is missing. Then write 8 distinct prompts, each 75 to 135 words, with its own square-bracket inputs, title, and one-line use case. Include prompts for: a job-description review; structured interview questions and scorecard; a performance-conversation agenda; manager feedback on a documented issue; an employee communication about a policy change; a learning plan; an engagement-survey synthesis; and an offboarding or exit-interview question set.
Each prompt must request practical outputs with clear sections, decision criteria, owners, dates, and wording appropriate to the audience. For hiring and performance work, require job-related evidence, consistent criteria, and separate factual observations from interpretation. For policy or employment-law topics, require the AI to identify questions for qualified HR, legal, payroll, benefits, or labor-relations review rather than present legal conclusions. Do not ask it to infer protected characteristics, diagnose health conditions, rank people from unverified data, or create a rationale after a decision has already been made. Before answering, check that every prompt avoids confidential personal data unless redacted and that no prompt encourages a discriminatory, retaliatory, or unsupported employment action.
Fill in
| Placeholder | What to enter | Example |
|---|---|---|
| [ORGANIZATION CONTEXT] | Describe your organization’s size, industry, workforce mix, and the HR team’s role. | A 180-person U.S. software company with hybrid product, sales, and support teams; two HR business partners and outsourced payroll. |
| [JURISDICTION AND POLICY CONTEXT] | Enter relevant work locations, union or works-council context, and internal policies that must be followed. | Employees in California, New York, and Texas; no union; handbook requires HR review of performance-improvement plans and terminations. |
| [HR PRIORITIES] | List the people processes or current problems the prompt library should address. | Hiring customer-support managers, improving manager feedback, revising a remote-work announcement, and summarizing an engagement survey. |
| [COMMUNICATION AND PRIVACY RULES] | Describe the organization’s writing style, approval requirements, and data that must not be entered into AI tools. | Direct, respectful tone. Never paste medical information, compensation spreadsheets, investigation notes, candidate identifiers, or employee relations allegations. HR director approves policy announcements. |
How to use
- Replace the four context fields with the actual boundaries of your organization and AI policy.
- Select the prompt matching the task and enter redacted, job-relevant source material only.
- Check that the output separates evidence, recommendations, and items needing counsel or policy review.
- Follow up with: “Revise this for managers who need a 15-minute version and retain only job-related criteria.”
Variations
Interview scorecard
Use before interviewing candidates for a defined role.
Create a structured interview kit for [ROLE] using this approved job description: [JOB DESCRIPTION]. The must-have competencies are [COMPETENCIES], and interviewers will be [INTERVIEW PANEL]. Produce 6 behavioral or work-sample questions, neutral follow-ups, a 1–4 anchored scorecard, and a debrief template. Tie every question to a stated competency; exclude questions about protected characteristics, family, health, age, citizenship beyond authorized work eligibility, or other non-job factors. Flag any competency that is vague or unsupported by the description.
Policy announcement
Use to draft an internal announcement after policy text is approved.
Draft an employee announcement explaining this approved policy change: [APPROVED POLICY TEXT]. The audience is [AUDIENCE], the effective date is [DATE], and the required actions are [EMPLOYEE ACTIONS]. Produce a subject line, a 250-word email, a manager FAQ, and a short acknowledgment reminder. Explain what changes, who is affected, and where employees can get help; do not add promises, interpretations, or legal conclusions beyond the policy. Flag ambiguous clauses for HR or legal review before distribution.
Performance meeting
Use to prepare a documented, fair manager conversation.
Prepare a performance-conversation agenda using these documented facts: [FACTS AND EXAMPLES]. The employee’s role expectations are [ROLE EXPECTATIONS], prior support provided was [PRIOR SUPPORT], and the meeting goal is [MEETING GOAL]. Produce a neutral opening, fact-based discussion points, questions for the employee, specific next steps, support offered, and a written recap template. Separate observed behavior or results from interpretation. Do not diagnose motives, promise an outcome, or recommend discipline; flag matters needing HR review.
Tips
- Use approved job competencies to design interview questions before candidates are seen, then score evidence rather than overall impressions.
- For performance discussions, retain dates, expectations, examples, prior coaching, and employee responses; AI can organize this record but cannot replace it.
- Redact names, health information, allegations, compensation details, and investigation material unless your approved AI environment expressly permits it.
- Treat generated policy language as a draft until HR, legal, payroll, benefits, or labor-relations owners have reviewed the relevant sections.
FAQ
Can AI write a termination letter or performance-improvement plan?
It can help structure a draft from approved facts and templates, but HR and legal review are important because requirements vary by jurisdiction and circumstance.
Can I paste employee survey comments into AI?
Use only anonymized, aggregated comments and remove details that could identify an employee. Be especially cautious with small teams and open-text responses.
Can AI decide which candidate to hire?
No. It can organize job-related evidence against a pre-set scorecard, but the hiring decision should remain with accountable people using consistent criteria.