Prompts for Life · Pack 10 · 10 prompt templates

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AI Prompts for Your Job Search: Resume, Cover Letter and Interview

The Career & Job Search pack: 10 AI prompt templates for ChatGPT, Claude and Gemini

Get ready for every step of your job search. Tell the job search prompts what you have done and which job you want, and get a résumé with a number in every line, a LinkedIn profile, a cover letter written for one employer, interview answers built from your own stories and a plan to negotiate your salary.

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  • Best in Claude: a finished Word or Excel file from every prompt

Free guide: A cover letter with ChatGPT that doesn’t read as AI

Real exampleWord résumé · Prompt 03

“Responsible for warehouse operations and a team of 45.”

Dana Okafor — Senior Operations Manager

Dana Okafor’s résumé as a one-page Word document: one column, standard headings, dates right-aligned
Dana-Okafor-Resume.docxSee the finished files →

Benefits of the job search prompts

What the Job Search AI Prompts Do for You

Four things the job search prompts do for every application, from the first résumé line to the salary talk.

Prove every claim with a number

Each résumé line carries a number, a named result or a fact an employer can check. Empty words like “results-driven” are cut, and a missing number is asked for, never made up.

Tailor every application

Each résumé and cover letter is written for one role at one employer, in the words of the job listing. A generic application tells the hiring manager you did not read theirs.

Walk into the interview prepared

The interview prompts build a bank of true stories in STAR form (Situation, Task, Action, Result), run a mock interview and score your answers.

Negotiate the whole offer

The offer and salary negotiation prompts value the full package, base pay, bonus, retirement match, equity and benefits, and compare it with market pay before you answer.

Who the job search prompts are for

  • Professionals looking for their next role
  • Anyone whose role was cut and who needs to restart a search
  • Managers aiming for a more senior job
  • People changing career or industry
  • Anyone preparing for a job interview
  • Anyone weighing a job offer or negotiating salary

What is in the pack

10 Job Search Prompts: From Your Target Role to the Signed Offer

Each job search prompt works on its own. The prompt asks for what is needed and, in Claude, returns a finished Word or Excel file. Run the one you need, or run all ten in order.

  1. TargetPrompts 01–02
  2. PositionPrompts 03–04
  3. ApplyPrompts 05–06
  4. InterviewPrompts 07–08
  5. OfferPrompts 09–10
01Target

Career Assessment: Choose Your Target Role

Turns your experience into one target role, with the evidence that you can win it and the pay it commands.

Skills inventoryTarget rolePositioning statement

See it in Dana’s example
02Target

Job Market Research: Which Employers to Target

Builds a ranked list of employers to target, and reads market pay for your role from the listings and data you paste.

Market payRequirements patternTarget employer list

See it in Dana’s example
03Position

Résumé Bullets That Show Results (XYZ Format)

Rewrites your résumé so every line states a measured result, then builds it as a best-practice Word document.

XYZ formatATS keywordsWord document

See it in Dana’s example
04Position

LinkedIn Profile: Get Found by Recruiters

Rewrites your LinkedIn profile so recruiters searching for your target role find you and contact you.

Recruiter searchHeadlineAbout section

See it in Dana’s example
05Apply

Tailored Cover Letter

Writes a one-page cover letter for one listing, matching its top requirements to your proven results, as a Word document to match the résumé.

Requirement matchEmployer problemTone check

See it in Dana’s example
06Apply

Networking Messages: Introductions and Referrals

Writes the outreach messages and call plan that turn people you know into introductions and referrals.

Informational interviewReferralOutreach tracker

See it in Dana’s example
07Interview

Interview Prep: Answers Using the STAR Method

Builds a bank of true stories in STAR form, mapped to the questions the target role’s interviewers will ask.

STAR methodCompetency mapStory bank

See it in Dana’s example
08Interview

Mock Interview & Answer Scoring

Runs a realistic mock interview, scores each answer against a rubric, and rewrites the weakest answers.

Scoring rubricFollow-up probesReadiness call

See it in Dana’s example
09Offer

Compare Job Offers: Total Pay Side by Side

Values each offer as total compensation, and compares it with your floor, the market and your goals.

Total compensationExpected bonusWeighted comparison

See it in Dana’s example
10Offer

Salary Negotiation: Plan and Script Your Counter-Offer

Plans and scripts the counter-offer: the number, the evidence, the words and the fallback positions.

BATNACounter-offerTrade list

See it in Dana’s example

Worked example

Job Search Prompts Example: One Job Search, All 10 Prompts

Dana Okafor ran operations for two warehouses at Halden Freight in Columbus, Ohio, for eight years. Her role was eliminated on 13 March 2026. Over the next 11 weeks she sent the same résumé and the same cover letter to 140 operations jobs, reached 3 first-round interviews and received no offers: 11 weeks without pay, $20,300 at her old salary of $96,000. On 1 June she started again with one target role. Here is how the ten prompts took her from that search to a signed offer at $109,000, one step at a time.*

140applications sent with the same résumé
2.1%became interviews: 3 of 140
0offers after 11 weeks
$20,300of pay lost at her $96,000 salary

Prompt 01 · Target

Career Assessment: How Dana Used It

What Dana brought · her résumé and notes

“Eight years running warehouses. I’ve applied to any operations manager job I could find — 140 of them.”

What the prompt returned

One target: Senior Operations Manager in e-commerce fulfilment or third-party logistics. Her three interviews all came from that kind of role.

Search so far
140 applications to 9 job titles in 6 industries
Where interviews came from
3 of the 17 fulfilment roles; none of the other 123
Proven results
order-to-ship time −40%; overtime cost −$310K a year; WMS live at 2 sites
Target role
Senior Operations Manager, e-commerce fulfilment or 3PL, 200–2,000 staff, hybrid in Columbus

Takeaway: choose the target from the results you can prove, then aim every application at it.

The analysis · A search aimed at every job cost Dana 11 weeks and $20,300

A target role is a specific title, level, industry and location that a candidate can prove they are ready for today. Third-party logistics (3PL) companies run warehousing and shipping for other businesses.

  • 140 applications, 9 job titles: Dana applied to anything with “operations” in the title, from manufacturing to hospitals. 3 of 140 became interviews: 2.1%.
  • 17 fulfilment roles, all 3 interviews: every interview came from e-commerce fulfilment, where her results fit. That is 3 of 17 (18%), against 0 of the other 123.
  • 11 weeks without pay: at her old salary of $96,000, the unfocused search cost $20,300 before a single offer.

Prompt 02 · Target

Job Market Research: How Dana Used It

What Dana brought · 31 job listings

“I pasted 31 listings for senior operations roles around Columbus, and two salary surveys.”

What the prompt returned

Median posted midpoint $104,000. WMS experience appears in 24 of the 31 listings; her résumé never used the term.

Market pay, 31 listings
midpoints $88,000–$126,000; median $104,000; most between $96,000 and $112,000
Dana’s floor
$92,000: $12,000 below the median
Top requirements
WMS experience in 24 of 31 (77%); peak-season planning in 19 of 31 (61%)
Target list
24 employers: 6 through a former colleague, 12 direct, 6 to watch

Takeaway: read pay and requirements from many listings before writing a single application.

The analysis · Her pay floor sat $12,000 a year below the market

Market pay is read from the midpoint of many posted pay ranges, never from one listing. A requirements pattern counts how often each requirement appears across listings, so the résumé can answer the common ones first.

  • $92,000 floor, $104,000 median: Dana had set her minimum from her old pay, not the market. Accepting at her floor would have cost $12,000 a year, $36,000 over three years.
  • WMS in 24 of 31 listings: a warehouse management system (WMS) is the software that runs stock and picking. Dana had led a WMS rollout, but her résumé called it “system implementation”.
  • 24 target employers, 6 with a contact: the screen cut 60 employers to 24 in three tiers, and six had a former colleague of hers inside.

Prompt 03 · Position

Résumé Bullets That Show Results (XYZ Format): How Dana Used It

What Dana brought · her résumé

“Responsible for warehouse operations and a team of 45.”

What the prompt returned

“Cut order-to-ship time from 52 to 31 hours (−40%) across 2 warehouses and 45 staff by redesigning pick routes and shift start times.”

Numbers on the résumé
2 in 14 bullets
Left off entirely
$310K a year cut from overtime, recorded only in her 2023 review
Listing terms named
4 of the 13 in Larkspur Home’s listing
Rewritten
7 bullets, each with a number; 11 of 13 listing terms; one page, one column, in Word

Takeaway: put a number in every line, in the listing’s own words, and check every number can be defended.

The analysis · Her largest result, $310K a year, was not on her résumé

The XYZ format writes each bullet as: accomplished X, as measured by Y, by doing Z. An applicant tracking system (ATS) is the software employers use to store applications and rank them against the listing’s words.

  • 2 numbers in 14 bullets: the old résumé listed duties. A recruiter could not tell what Dana had changed, or by how much.
  • $310K a year, missing: her demand-based shift planning cut overtime cost by $310K a year. It was in a performance review, not on the résumé she sent 140 times.
  • 4 of 13 listing terms: the résumé named 4 of the 13 requirements in Larkspur’s listing, and a two-column layout the ATS read as one scrambled line. The rebuilt Word file is one column, with standard headings and real Word bullets.

Prompt 04 · Position

LinkedIn Profile: How Dana Used It

What Dana brought · her LinkedIn profile

“My headline says ‘Operations Manager at Halden Freight’. I haven’t touched the profile since 2019.”

What the prompt returned

“Senior Operations Manager | E-commerce Fulfilment & 3PL | Cut order-to-ship time 40% across 2 warehouses.”

Headline
her old job at the employer that had eliminated her role
Skills, in order
Microsoft Office first; WMS not listed
About section
empty
Rewritten
target-role headline; 11 listing terms in the skills; three results in the first lines

Takeaway: write the headline for the role you want, in the words recruiters search for.

The analysis · Recruiters sent no messages in 11 weeks

Recruiters find candidates by searching titles, skills and locations, so a profile is ranked on those words before anyone reads it. The headline is the line under your name that appears in every search result.

  • 0 recruiter messages in 11 weeks: the headline named a job Dana no longer had, at a freight company, so searches for fulfilment managers did not surface her.
  • 6 messages in the next 4 weeks: after the rewrite, recruiters searching “fulfilment”, “3PL” and “WMS” found the profile.
  • One mismatch fixed: the profile gave her start date at Halden as 2017; the résumé said 2018. The check caught it before a recruiter did.

Prompt 05 · Apply

Tailored Cover Letter: How Dana Used It

What Dana brought · Larkspur Home’s listing

“The listing asks for peak-season planning, a WMS rollout and cost control.”

What the prompt returned

A letter of under 200 words that opens on Larkspur’s shipping delays of up to 18 days last December, and answers each requirement with one result.

Old letter
the same 410 words sent with all 140 applications
Peak-season planning
2025 peak at 1.8× normal daily orders, order-to-ship held under 36 hours
WMS rollout
live at 2 sites on schedule; pick accuracy 97.1% to 99.4%
Cost control
overtime cost cut by $310K a year

Takeaway: write each letter for one employer’s problem, and prove each requirement with one number.

The analysis · One letter for 140 jobs produced 3 interviews

A cover letter answers one question: why this candidate, for this job, at this company. It opens with the employer’s problem and matches the listing’s top three requirements to three proven results.

  • 410 words, 140 times: Dana’s old letter named no employer’s problem and could have been sent anywhere. It was: 3 interviews from 140.
  • 18-day delays: Larkspur Home’s holiday shipping delays were in the news Dana pasted. The new letter opens on them and on her 2025 peak season.
  • 7 interviews from 26: her 26 tailored applications led to 7 first interviews (27%), against 3 of 140 before (2.1%).

Prompt 06 · Apply

Networking Messages: How Dana Used It

What Dana brought · her contact list

“I have former colleagues at 6 of my 24 target employers, but I haven’t spoken to most of them in two years.”

What the prompt returned

18 messages to former colleagues and people they introduced: 7 replies, 4 informational calls, 2 referrals.

First 11 weeks
0 messages to anyone at a target employer
Messages sent
18, each under 100 words, each with one small request
Replies and calls
7 replies (39%), 4 twenty-minute calls
Referrals
2: Larkspur Home and Brisk Parcel; both led to interviews

Takeaway: ask for information first, and a referral only after a useful conversation.

The analysis · Six contacts at target employers went unused for 11 weeks

An informational interview is a 20-minute conversation to learn how a team works and what it needs; it is not a request for a job. A referral is an employee putting your name forward to the hiring manager.

  • 6 contacts, 0 messages: Dana had former colleagues at 6 of her 24 target employers and contacted none of them during her first search.
  • 18 messages, 2 referrals: 7 people replied and 4 agreed to a call. Two offered to refer her after the call, without being asked in the first message.
  • 2 referrals, 2 interviews: both referrals reached a first interview. The 140 cold applications had reached 3.

Prompt 07 · Interview

Interview Prep: How Dana Used It

What Dana brought · her interview notes

“My notes had four stories, and all of them started with ‘we’.”

What the prompt returned

A bank of 9 STAR stories covering 10 competencies, each under two minutes spoken, each ending on a number.

Before
4 stories, all told as “we”, 1 with a result
Gap found
“leading through change”: no story
Story built for it
her 2024 WMS rollout, told through her own decisions
Coverage
9 stories, 10 competencies; all 14 questions in the Larkspur panel covered

Takeaway: prepare a small bank of true stories, each told in the first person and ending on a result.

The analysis · Three interviews in her first search ended in the first round

The STAR method structures an interview answer as Situation, Task, Action and Result. Behavioural questions (“tell me about a time…”) ask for past examples, and trained interviewers score each answer against set criteria.

  • 3 interviews, 0 second rounds: in her first search Dana answered from memory, and none of the three interviews went further.
  • 4 stories, all “we”: an interviewer cannot score a team’s action. Every story was rewritten around what Dana decided and did.
  • 14 questions, 9 stories: Larkspur’s panel asked 14 questions. The nine stories covered all of them, because one good story answers several.

Prompt 08 · Interview

Mock Interview & Answer Scoring: How Dana Used It

What Dana brought · her practice answers

“Score my answers to the questions Larkspur’s panel is likely to ask.”

What the prompt returned

First run: 2.4 out of 5 on measured result. After the three weakest answers were rewritten: 4.1.

Measured result
2.4 out of 5 on the first run
Pattern
“we” for her own actions in 6 of 8 answers
Length
3 minutes 40 seconds on average; the rubric allows 2
After rewrites
4.1 out of 5; 11 numbers across the eight answers, up from 2

Takeaway: rehearse against a written rubric, and fix the pattern that runs through every answer.

The analysis · Eight answers carried 2 numbers between them

A scoring rubric sets out in advance what a weak, adequate and strong answer contains, so the score reflects evidence rather than impressions. This one scores structure, personal action, measured result and relevance.

  • 2.4 on measured result: most answers ended on effort (“we worked really hard”) instead of a figure. An answer with no number cannot score above 3.
  • 6 of 8 answers said “we”: the pattern ran through the whole run, so it was fixed once, across every story, not answer by answer.
  • 3 minutes 40 seconds: long answers lost the point before the result. The rewrites put the result in the first 30 seconds.

Prompt 09 · Offer

Compare Job Offers: How Dana Used It

What Dana brought · two offers

“Corvid Logistics offers $110,000 base. Larkspur offers $104,000 plus a 10% bonus target.”

What the prompt returned

Larkspur is worth $115,120 a year and Corvid $107,300. The lower base salary is the better offer by $7,820.

Base salary
Larkspur $104,000 · Corvid $110,000
Expected bonus
Larkspur $9,360 (10% target, 90% average payout) · Corvid none
Retirement match, less health premiums
Larkspur 4% ($4,160) less $2,400 · Corvid 3% ($3,300) less $6,000
Total compensation
Larkspur $115,120 · Corvid $107,300

Takeaway: value every offer in full, with the bonus at its real payout rate, before comparing base salaries.

The analysis · Choosing on base salary would have cost $7,820 a year

Total compensation is everything an employer pays for your work in a year: base, expected bonus, retirement match, equity and benefits, less the costs the job adds. Expected bonus is the target multiplied by the historical payout rate.

  • $6,000 more base at Corvid: on base salary alone Corvid looked better, $110,000 against $104,000.
  • $9,360 of expected bonus: Larkspur’s 10% bonus has paid out at 90% of target on average for three years, so it is valued at $9,360, not the full $10,400.
  • $3,600 in health premiums: Corvid’s plan costs Dana $6,000 a year against Larkspur’s $2,400. With the higher match, Larkspur wins by $7,820 a year.

Prompt 10 · Offer

Salary Negotiation: How Dana Used It

What Dana brought · Larkspur’s recruiter

“Larkspur’s recruiter called to ask whether $104,000 works.”

What the prompt returned

A counter at $112,000, backed by Corvid’s $110,000 base and her results. Agreed: $109,000 base and a $5,000 signing bonus.

Opening offer
$104,000 base, the market median
BATNA
Corvid’s offer: $110,000 base
Counter named
$112,000 base; signing bonus as the trade if base could not move
Agreed
$109,000 base + $5,000 signing bonus: $10,000 more in year one

Takeaway: counter once, with one number backed by market pay and your alternative, and confirm it in writing.

The analysis · Saying yes on the call would have left $10,000 on the table

BATNA stands for best alternative to a negotiated agreement: what you will do if this negotiation fails. A strong BATNA, such as a competing offer, sets how firmly you can push.

  • “Does $104,000 work?”: the question invites a yes. Accepting would have left the $5,000 base increase and the $5,000 signing bonus unasked.
  • $5,000 a year, every year: the higher base also raises the expected bonus by $450 and the retirement match by $200 a year.
  • $109,000 signed: $13,000 above her old salary of $96,000, and $17,000 above the floor she had set in March.
The finished files · from prompts 03, 05 and 10

The Finished Files: Résumé, Cover Letter and Salary Negotiation Email

Three documents from Dana’s ten prompts: the Word résumé from prompt 03, the Larkspur cover letter from prompt 05, and the counter-offer email from prompt 10.

Dana Okafor — Senior Operations Manager

E-commerce Fulfilment & 3PL · Columbus, Ohio · hybrid

Dana-Okafor-Resume.docx
1 page · 7 bullets, 7 with numbers

Dana Okafor’s résumé as a one-page Word document: one column, standard headings, dates right-aligned
The Word file, built in Claude to prompt 03’s formatting specification.
BeforeRewritten in XYZ format
Responsible for warehouse operations and a team of 45.Cut order-to-ship time from 52 to 31 hours (−40%) across 2 warehouses and 45 staff by redesigning pick routes and shift start times.
Managed overtime and labour scheduling.Reduced overtime cost by $310K a year by moving 2 sites to demand-based shift planning.
Led system implementation project.Led the WMS rollout at 2 sites in 2024, live on schedule; pick accuracy rose from 97.1% to 99.4%.
Handled peak season.Ran the 2025 peak season at 1.8× normal daily orders with order-to-ship time held under 36 hours.

Larkspur Home — Senior Operations Manager, Fulfilment

Cover letter · sent as the email body with the résumé attached

Under 200 words
Referred by Jordan Blake

Subject: Senior Operations Manager — ran peak at 1.8× volume, order-to-ship under 36 hours

Dear Ms Reyes,

Larkspur’s customers waited up to 18 days for holiday orders last December. I ran Halden Freight’s two Columbus warehouses through the 2025 peak at 1.8 times normal daily orders, and order-to-ship time stayed under 36 hours. Jordan Blake, who worked with me at Halden, suggested I write to you about the Senior Operations Manager role.

Your listing asks for three things, and each is something I have done:

Peak-season planning. I rebuilt our pick routes and shift start times, cutting order-to-ship time from 52 to 31 hours across both sites, before volume nearly doubled.

A WMS rollout. I led the move to a new warehouse management system at two sites in 2024. It went live on schedule, and pick accuracy rose from 97.1% to 99.4%.

Cost control. Moving both sites to demand-based shift planning cut overtime cost by $310K a year.

I would welcome 30 minutes to discuss how I would plan Larkspur’s next peak season.

Yours sincerely,
Dana Okafor

Counter-offer — email to Larkspur’s recruiter

One counter, one number, one fallback

Offer: $104,000 base
Counter: $112,000

Subject: Senior Operations Manager offer — base salary

Hi Sam,

Thank you for the offer. I’m excited about the role and about helping Larkspur through its next peak season.

Before I accept, I’d like to discuss the base salary. I have a competing offer at $110,000 base. I also bring the WMS rollout your listing puts first: at Halden it went live on schedule at two sites and raised pick accuracy from 97.1% to 99.4%.

With that in mind, I’m asking for a base salary of $112,000. If base is fixed at this level, a signing bonus would close the gap.

Larkspur is my first choice, and I’d like to confirm this week. Could we speak on Thursday?

Best regards,
Dana

Prompt output, formatted for this page. In Claude each prompt returns it as a finished Word or Excel file; other tools return the same content as text and tables. The figures come from whatever you paste in. Dana Okafor is fictional, so every number here is ours to show you.

Job Search AI Prompts: Frequently Asked Questions

Can ChatGPT write my résumé and cover letter?

Yes. The job search prompts ask for your experience and the job listing, then write résumé lines with numbers and a cover letter for that one employer. A missing number is asked for, never made up. In Claude, both come back as Word documents.

Will the cover letter sound like AI?

The cover letter prompt writes for one role at one employer, in the words of its listing and from your real results, and cuts generic phrases. Read the letter and adjust it to your own voice before you send it.

Do the prompts help with salary negotiation?

Yes. Prompt 9 values each offer in full and compares it with the market. Prompt 10 plans the counter-offer: the number, the evidence, the words and the fallback. Nothing on this page is legal, financial or tax advice.

Which AI tools do the job search prompts work with?

ChatGPT, Claude and Gemini. The pack works best in Claude, where the résumé and cover letter are built as Word documents.

Pack 10 · Career & Job Search

Get the Job Search AI Prompt Pack

  • Career assessment, target role, employer and job market research
  • Résumé achievement bullets and LinkedIn profile, with the résumé and cover letter built as Word documents in Claude
  • Tailored cover letter, networking and referral outreach
  • STAR interview preparation, mock interview scoring, offer evaluation, salary negotiation
  • Text file and formatted PDF · ChatGPT, Claude and Gemini · best in Claude
  • Every prompt ends in a finished Word or Excel file in Claude

* Dana Okafor, Halden Freight, Larkspur Home, Corvid Logistics, Brisk Parcel, the people named and all figures on this page are fictional and used for illustration only. Output from these prompts depends on the information you supply and the AI tool you use. Pay, benefits and employment rules differ by country and state; nothing on this page is legal, financial or tax advice.

More AI Prompts for Everyday Life

Nine packs for everyday life, from career and money to travel and health, each written to the same standard with its own worked example.