Resume tailoring prompt builder
A resume that wins interviews speaks the language of the specific job, not a generic version of your career. This builder produces a precise prompt that instructs an LLM to tailor your existing resume to one job description — surfacing the most relevant experience, mirroring the posting’s terminology, and reordering bullets so the strongest match sits on top. It never asks the model to invent experience, only to present what is already true in the most relevant order.
How it works
You paste the job description and your current resume sections, then pick how aggressively to rewrite and what output format you want. The tool assembles a structured prompt with three things the model needs: the target role’s requirements and keywords, your real material, and explicit guardrails. The guardrails matter most — the prompt tells the model to extract required skills from the posting, map them to your genuine experience, rephrase bullets for impact, and flag any required skill you appear to lack rather than fabricate it. Everything runs in your browser; nothing is sent anywhere until you paste the prompt into ChatGPT, Claude, or another model.
Why tailoring per application matters
Most job applications are filtered by applicant tracking systems before a human reviews them. ATS filters often match resumes against keywords extracted from the job description. A resume that uses “programme management” when the posting says “program management,” or “data visualisation” when the role asks for “data visualization,” can score lower than a technically weaker candidate who mirrors the exact phrasing.
The deeper benefit of tailoring goes beyond keyword matching: a recruiter reading 80 resumes for a single role will spend more time on the ones where the experience clearly lines up with the requirements, and less on the ones that seem generic. When your strongest relevant experience appears in the first three bullets rather than buried in the third job, the reader’s initial assessment changes.
A tailoring prompt does this systematically, for every application, without inventing anything.
The three depth levels explained
Light keeps your existing wording mostly intact. It reorders bullets so the most relevant experience appears first and adjusts emphasis without significantly rephrasing. Use this when your master resume is already well-written and the role is a close match.
Moderate rephrases bullets to better mirror the posting’s language and tightens the summary to emphasize the most relevant two or three signals. This is appropriate for roles that are a strong match but not a perfect one — where some translation is needed between your experience framing and the posting’s framing.
Aggressive restructures sections, rewrites the summary for the specific role, and reorders or consolidates job history to foreground the most relevant experience. Use this when applying for a role that is a genuine stretch, or when your master resume is organized around a different emphasis than this posting requires. Review the output carefully at this depth.
Output format: when to use each
Tailored bullets outputs a list of revised bullets for each section. Use this when you want to paste improvements one at a time into an existing document rather than replacing everything.
Full document outputs a complete resume ready to paste or copy. Use this when you want a single clean draft for final polishing.
Change list outputs a structured list of what was changed and why. Use this the first few times to build confidence in the model’s output before accepting changes without reviewing them. It is the safest format when using aggressive depth.
Practical tips
- Run a separate prompt for each application. The alignment benefit disappears with a generic prompt.
- If the model flags a required skill you lack, do not ask it to hide the gap — address it directly in a cover letter or in the summary as a growth area.
- If the output claims experience you do not have, the prompt was too aggressive or your master resume lacked enough context to prevent extrapolation. Dial back the depth and try again.
- Keep your master resume as long and complete as possible. The model cannot surface experience that is not in the input material.