Copy-ready prompts: from job posting to tailored resume in one chat

Why a plain chat prompt is not enough

"Rewrite my resume for this job" works in any chat, and the result usually reads well. The trouble is what you cannot see. A model asked to match a posting will happily add a tool you have never used, round a number up, or retitle a past job to match the new one. None of it is flagged, and nothing is saved anywhere you can track.

With Lamr connected, the same request runs Lamr's tailoring instead. It starts from your saved master resume, keeps your past job titles as written, does not add numbers your resume does not contain, and returns a fit score with the requirements you do not meet listed as gaps. The draft is saved to an application, so the documents, the posting and the outcome stay together.

The prompts below assume Lamr is already connected. If it is not, the setup guide takes about two minutes.

Step 1: Decide whether it is worth your time

Screening compares the posting with your real background, requirement by requirement, and saves the score to the application. It costs 1 credit.

Track this job in Lamr and screen my fit. Use the full posting below, not a summary. Give me my fit score, the requirements I meet, the ones I only partly meet, and the ones I don't. Then tell me honestly whether it's worth tailoring for. Don't draft anything yet.

Link: [job posting URL, if you have one]

Posting:
[paste the full job posting]

When you have several postings open in tabs, screen them together and let the scores pick for you:

I'm pasting [3] job postings below, separated by lines of dashes. Track each one in Lamr and screen my fit for each. Then rank them by fit score in a short table with the main gap for each, and recommend which ones to tailor for. Don't draft anything.

[posting 1]
----------
[posting 2]
----------
[posting 3]

Fit scores use the same scale everywhere in Lamr, so a 78 here means the same as a 78 on any other application.

Step 2: Draft the documents

Drafting writes a tailored resume and cover letter from your master resume and saves them as an editable draft. It costs 5 credits, or 3 if the application only needs one document. Nothing is turned into a PDF yet.

Draft my tailored resume and cover letter for the [Company] application in Lamr. Then tell me: what changed compared with my master resume, which requirements are still gaps, and any numbers it suggests I could add if I have them. Don't compile yet.

Some applications do not want a cover letter. Turning it off first makes the draft cheaper:

The [Company] application doesn't need a cover letter. Turn the cover letter off for that application in Lamr, then draft only the resume. Don't compile yet.

You can also set how far the rewrite goes, for this draft only: light keeps your wording, balanced is the default, and aggressive pushes hardest toward the posting's language. All three keep the same rules about facts.

Draft the [Company] resume in Lamr with light rewrite intensity. I want it to still sound like me. Don't compile yet.

Step 3: Review before you compile

This is the step people skip, and the one that matters most. A tailored resume goes out under your name, so read what changed before it becomes a PDF.

Before compiling the [Company] draft, show me the summary and every bullet that differs from my master resume, side by side. Then list each requirement from the fit analysis that's marked partial or missing. Don't compile.

For small changes, you can ask in the chat. Anything you add should be true, because this edit happens after Lamr's tailoring step. For larger edits, the draft editor in the Lamr app is quicker.

In the [Company] draft, change the summary so it opens with [a skill or result I genuinely have]. Keep everything else exactly the same, show me the new summary, and wait for my OK before compiling.

Step 4: Compile and read the finished documents

Compiling typesets the reviewed draft into a PDF and saves it to the application. It is free, and so is recompiling in a different template: classic, modern or sidebar.

Compile the [Company] draft in Lamr with the [classic] template. Then show me the final resume and cover letter as text so I can read them here.

Recompile my [Company] documents in Lamr with the modern template and the navy accent.

Your assistant can read the finished wording directly, without downloading the PDF. To attach the file to an application form yourself, download it from the application in Lamr.

Step 5: Answer the form's own questions

Many forms add questions of their own: why this company, a time you disagreed with a decision, a 500-character limit. Lamr drafts answers from your real background and saves them to the application. It costs 3 credits for the set, and 1 to redraft a single answer.

Here are the extra questions from the [Company] application form, with their character limits where the form shows one. Draft answers in Lamr and show them to me. Answer from my actual experience only.

[paste the questions]

Redraft answer [2] for [Company] in Lamr. Make it more specific and keep it under [500] characters.

Step 6: Prepare for the interview

When an application turns into an interview, Lamr can predict the questions you are most likely to face, weighted toward the gaps from your fit analysis, each with an honest angle based on what you have actually done. It costs 2 credits. The practice round in the second prompt is your assistant's own work and costs nothing extra.

My [Company] application moved to interview. Update its status in Lamr, then generate interview prep for it and show me the questions grouped by category.

Using the [Company] interview prep in Lamr, quiz me on the three questions tied to my biggest gaps, one at a time. Wait for my answer each time, then tell me what was strong and what to tighten.