📁 HR
Recruiting Prompt: Intake Notes to Sourcing and Screen Plan
Turn a hiring manager intake call into a recruiting plan: must-haves, sourcing channels, search strings, pipeline math, a screen guide, and a weekly update.
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Prompt
Act as an in-house technical recruiter who turns a messy hiring manager intake call into a search plan the whole team can follow, and who keeps every screening step tied to the job, not to the person. Inputs: - Intake call notes, as typed during the call: [RoleIntakeNotes] - Requirements the hiring manager called must-have, and the ones they called nice-to-have: [MustHaves] - Pay range, location, and remote or hybrid policy: [CompensationAndLocation] - Number of hires and target start date: [HiringTimeline] - Funnel ratios from our own ATS for similar past roles: [PipelineHistory] - Sourcing channels we can use, with budget or seat limits: [SourcingChannels] - How we run first-round screens (length, phone or video, who joins): [ScreenFormat] Generate: 1. Intake summary: the role in three sentences, and a list of open questions to send back to the hiring manager where RoleIntakeNotes are vague or contradict MustHaves. 2. Requirements check: keep must-haves to five or fewer. For each one, say how a recruiter would see evidence of it in a resume or a screen. Flag requirements that may screen out qualified people without being needed for the work (degree requirements, years of experience used as a proxy, specific company names) and suggest a skills-based wording. 3. Sourcing plan per channel in SourcingChannels: who to look for, where, weekly volume, and who owns it. Add two search strings built only from skills and job titles in MustHaves. 4. Pipeline math worked backward from HiringTimeline using PipelineHistory: offers, final interviews, screens, applicants, and outreach needed, with each step shown. Then the weekly targets. 5. Phone screen guide for ScreenFormat: logistics questions asked the same way to every candidate (pay range fit, location or schedule fit, start date), then one question per must-have with what a strong answer includes. 6. A weekly update template for the hiring manager: pipeline counts by stage, what changed, decisions needed from them. 7. Fairness check on everything above. Rules: - AI drafts, people decide. Never rank, score, or reject candidates, and never suggest filters based on age, gender, race, religion, national origin, disability, pregnancy, or any other protected trait (in the US: Title VII, the ADEA, and the ADA). - Do not ask about salary history where local law bans it; ask about pay expectations against the range instead. - Use only numbers from PipelineHistory. If a ratio is missing, ask for it.
Instructions
Run this in ChatGPT, Claude, or Gemini with your own intake notes and ATS numbers. Replace every [bracket]. Leave candidate names and contact details out. The plan is a draft: recruiters and hiring managers make every screening and hiring decision, and you should check screen questions with your HR or legal team for your state and country.
Generated Output
This image was generated using the prompt above.
Examples
Example Input
RoleIntakeNotes: Senior data analyst for the payments team. Will own the weekly revenue dashboard and answer pricing questions from finance. Manager (Priya) wants someone who can push back on bad metrics. Said "ideally ex-fintech" and "10 years experience" but also said two of her best analysts had 4 years. Team uses SQL, dbt, and Looker. MustHaves: Strong SQL. Dashboard ownership end to end. Explaining numbers to non-technical stakeholders. Nice-to-have: dbt, Looker, payments or pricing data, Python. CompensationAndLocation: 125,000 to 145,000 base. Hybrid, 2 days a week in the Chicago office. HiringTimeline: 1 hire, offer accepted by early December. We start sourcing this week, 6 weeks of sourcing. PipelineHistory (last year's analyst roles): applicant to screen 10 percent. Outreach to reply 20 percent, reply to screen 50 percent. Screen to final interview 40 percent. Final interview to offer 25 percent. Offer accept 80 percent. SourcingChannels: LinkedIn Recruiter (1 seat, me), inbound job post, employee referrals, a local analytics meetup. ScreenFormat: 30 minute video call, recruiter only.
Example Output
1. INTAKE SUMMARY
Senior data analyst on the payments team who owns the weekly revenue dashboard, answers pricing questions from finance, and is confident enough to challenge weak metrics. Works in SQL, dbt, and Looker. Hybrid in Chicago, 2 days a week.
Questions for Priya:
- You mentioned 10 years of experience, but two of your best analysts had 4. Can we drop the number and screen for dashboard ownership instead?
- Is "ex-fintech" a must, or is any pricing or revenue data enough?
- Who signs off on dashboard changes today: this role or finance?
2. REQUIREMENTS CHECK
Must-haves (3):
- Strong SQL. Evidence: complex queries described in a resume bullet, or walking through one in the screen.
- Dashboard ownership end to end. Evidence: built and maintained a recurring dashboard, not only edited one.
- Explaining numbers to non-technical people. Evidence: a story about changing a stakeholder's mind.
Flags: "10 years" works as a proxy and conflicts with your own team's experience; suggest "has owned a production dashboard used weekly by business teams." "Ex-fintech" narrows the pool; keep payments or pricing data as nice-to-have.
3. SOURCING PLAN
- LinkedIn Recruiter (me): analysts and analytics engineers, Chicago area plus hybrid commuters, 12 messages a week.
- Job post: publish with the pay range, review applicants twice a week.
- Referrals: ask the payments and finance teams this week, with the 3 must-haves.
- Analytics meetup: attend the next event, collect interest, no cold lists.
Search strings:
("data analyst" OR "analytics engineer" OR "BI analyst") AND SQL AND (dashboard OR Looker OR Tableau)
("senior analyst" OR "revenue analyst" OR "pricing analyst") AND SQL AND (dbt OR "data modeling")
4. PIPELINE MATH (1 hire)
Offers: 1 / 0.80 = 1.25
Final interviews: 1.25 / 0.25 = 5
Screens: 5 / 0.40 = 12.5, plan 13
Split screens: 7 from outreach, 6 from applicants.
Outreach: 7 / (0.20 x 0.50) = 7 / 0.10 = 70 messages
Applicants: 6 / 0.10 = 60 applicants
Weekly targets over 6 weeks: 70 / 6 = 11.7, so 12 messages a week; 60 / 6 = 10 applicants a week; about 2 screens a week.
5. PHONE SCREEN GUIDE (30 minutes)
Same for everyone: "The base range is 125,000 to 145,000. Does that work for you?" "The role is hybrid, 2 days a week in Chicago. Does that work?" "When could you start?"
- SQL: "Walk me through the hardest query you wrote recently." Strong: explains the joins, how they checked the result, and what they would change.
- Dashboard ownership: "Tell me about a dashboard you owned." Strong: who used it, how often, how they handled a broken number.
- Explaining numbers: "When did you change a stakeholder's mind with data?" Strong: the situation, the data, and the outcome in plain words.
6. WEEKLY UPDATE TO PRIYA
Pipeline: outreach sent [n], replies [n], screens [n], final interviews [n], offers [n].
What changed: [one or two lines]
Need from you: [interview slots, feedback by date]
7. FAIRNESS CHECK
No age, school, or company filters. Years of experience replaced with evidence of the work. Logistics questions are identical for every candidate. No salary history question.