This resume gap-analysis Prompt compares your application to the job description first
Why this prompt matters
Most applicants lose interviews before a human conversation starts. Not because they are unqualified, but because their resume hides relevant work, misses obvious hiring signals, or over-focuses on the wrong experience. A structured Prompt reduces that waste by turning a vague editing task into a targeted rewrite based on how screening actually works.
What we use it for
You find a role you actually want, but the job description is dense and your resume is a rough all-purpose version. Before you apply, you want to know which requirements matter most, where your evidence is thin, and which edits will make the strongest difference in one pass.
Prompt
Role: Act as a senior recruiter and career coach who reviews resumes against job descriptions, identifies hiring-risk gaps, and rewrites weak experience bullets into sharper evidence of fit. Context: I am applying for a role and I need more than generic resume feedback. I want a structured comparison between my resume and the target job description so I can see where I look strong, where I look weak, what evidence is missing, and which edits will most improve my chances. The goal is not to flatter me. The goal is to think like a skeptical recruiter who has to screen dozens of candidates quickly. Task: Compare my resume to the target job description. Identify the role's must-have requirements, nice-to-have signals, and likely screening criteria. Then evaluate how well my current resume matches those requirements. Flag missing experience, unclear phrasing, weak bullets, missing metrics, and places where my wording hides relevant experience. Rewrite the weakest bullet points so they are sharper, more credible, and more aligned with the role. If a gap cannot be fixed honestly, say so and suggest the safest workaround in the application, portfolio, or cover letter. Constraints: - Do not invent experience, tools, degrees, certifications, metrics, or achievements that are not supported by my input. - Separate true qualification gaps from presentation problems. - Prioritize the fixes that would matter most in an initial recruiter screen. - Keep important terms in English when they are standard hiring or technical language, such as API, SQL, Python, SaaS, KPI, OKR, and Prompt. - If the job description is unrealistic or overloaded, say which requirements are likely flexible versus essential. - When rewriting bullets, keep them believable and concise. - Point out ATS keyword issues, but do not turn the resume into unreadable keyword stuffing. Output Format: 1. Role summary in 3 to 5 bullet points 2. Top screening criteria the recruiter will probably use 3. Match score from 0 to 100 with a short explanation 4. Strengths already visible in the resume 5. Real gaps that could block an interview 6. Presentation problems that make the resume look weaker than it is 7. Rewritten bullet points for the most important weak sections 8. Missing keywords or evidence to add carefully 9. Tailored application strategy for this specific role 10. Red flags or claims I should avoid making Inputs: - Job title: [TARGET ROLE] - Company type: [STARTUP / ENTERPRISE / AGENCY / PUBLIC SECTOR / OTHER] - Job description: [PASTE FULL JOB DESCRIPTION] - My current resume: [PASTE RESUME TEXT] - Seniority level: [ENTRY / MID / SENIOR / STAFF / EXECUTIVE] - Roles I most want to emphasize: [LIST] - Areas where I feel weak: [LIST] - Country or market: [LOCATION] - Any strict constraints: [NO DEGREE / CAREER GAP / INDUSTRY SWITCH / ETC.]
Result
1. Role summary - The role is a senior product analyst position in a B2B SaaS company focused on self-serve growth and lifecycle retention. - The employer wants someone who can work across SQL, experimentation, stakeholder communication, and dashboard design. - The description strongly suggests they value business judgment as much as technical analysis. - Experience partnering with product managers and marketing appears to matter more than pure BI reporting depth.
2. Top screening criteria the recruiter will probably use First, whether the candidate has clear evidence of ownership over product or growth analytics rather than generic reporting support. Second, whether they can show strong SQL and experimentation experience in a SaaS environment. Third, whether the resume proves business impact with metrics instead of task lists. Fourth, whether cross-functional communication is visible, especially with product, engineering, and go-to-market teams.
3. Match score 78/100. The resume shows strong analytics fundamentals, dashboard ownership, and stakeholder exposure, but it undersells experimentation work and does not clearly connect analysis to revenue or retention outcomes. The candidate looks plausible for interview, but not yet obvious.
4. Strengths already visible in the resume The candidate has four years of analytics experience, clear SQL usage, ownership of recurring executive reporting, and evidence of collaboration with product managers. The migration project bullet also signals comfort with messy systems and operational work.
5. Real gaps that could block an interview There is no direct mention of A/B testing design, retention analysis, or lifecycle funnel ownership, even though the job description emphasizes all three. Python appears only once and without context, which makes technical depth hard to judge.
6. Presentation problems Several bullets describe activity rather than outcome. Phrases like “supported dashboards” and “helped improve reporting” are too weak for a senior role. Important SaaS metrics such as activation, conversion, churn, or expansion are absent.
7. Rewritten bullet points - Replaced “Supported weekly dashboards for product leadership” with “Owned weekly product-performance dashboards used by leadership to track activation, retention, and conversion trends across the self-serve funnel.” - Replaced “Helped marketing with campaign reporting” with “Partnered with lifecycle marketing to analyze campaign performance, identify drop-off points, and inform retention experiments tied to reactivation goals.” - Replaced “Worked on data migration project” with “Led analytics validation during a cross-system data migration, reducing reporting discrepancies and restoring stakeholder trust in core KPI reporting.”
8. Missing keywords or evidence to add carefully Add any truthful experience tied to experimentation, cohort analysis, retention, funnel analysis, lifecycle metrics, and product decision support. If you used Python for notebook analysis or automation, say how.
9. Tailored application strategy Lead with product analytics, not general BI work. Move any experiment-related example higher on the page. If you do not have formal A/B ownership, use a cover letter or application note to show adjacent evidence such as hypothesis testing, funnel diagnosis, or post-launch measurement.
10. Red flags to avoid Do not imply ownership of experimentation programs if you only consumed results. Do not add growth metrics you cannot defend in an interview. Avoid stuffing the resume with every keyword from the posting if the underlying evidence is weak.
Most people do not need another generic resume review. They need a faster way to see how a specific job description will judge their application before a recruiter ever opens a phone screen.
That is what this Prompt is built for. It tells the model to act like a recruiter and career coach at the same time, then forces it to separate real qualification gaps from presentation problems. That distinction matters. A missing skill and a badly written bullet point are not the same problem, and they should not be fixed the same way.
The structure is deliberate. The Role frames the model as a skeptical reviewer, not a cheerleader. The Context explains that the task is role-specific rather than general career advice. The Task asks for screening criteria, match analysis, rewritten bullets, and practical application strategy. The Constraints do the most important work: they block the model from inventing achievements, fake metrics, or dishonest keyword stuffing just to make the resume look better.
The output format also makes this Prompt more useful than a one-shot rewrite. Instead of dumping a revised resume and moving on, it explains the likely screening logic behind the role, assigns a match score with reasoning, identifies true blockers, and rewrites the weakest sections first. That helps the reader spend time where it matters instead of polishing low-value details.
The example output shows the kind of diagnosis strong candidates actually need. It does not just say “tailor your resume.” It explains which signals a recruiter is likely to use, how a candidate can sound stronger without exaggerating, and where adjacent experience can be repositioned honestly. That is especially useful for career switchers, applicants targeting a stretch role, and people whose experience is better than their current wording makes it look.
If you are applying to roles selectively rather than spraying the same resume everywhere, this is a Prompt worth saving. It turns resume editing into a sharper decision process, and it can help you spot weaknesses before the hiring funnel does it for you.