Requirement-to-evidence map
See which job requirements have direct evidence, transferable evidence, weak proof, or no defensible support in your edited resume.
TL;DR — Paste a redacted resume and job description to generate role-matched interview questions, STAR story prompts, and evidence gaps — processed locally in your browser, nothing uploaded or saved.
Updated July 2026. Maintained by a small team of AI super-users who teach multi-AI research and study workflows to researchers, students, and professionals — no affiliate relationships. About this guide →Changelog
Remove personal details first. Then add your resume and target job description. The tool maps the edited text inside this browser to role requirements, likely questions, STAR story gaps, and a NotebookLM-ready preparation pack.
Create edited copies of the resume and supporting notes. Keep only the facts needed to prepare for the role.
Paste text or open a local file. The matching and scoring run inside the current browser tab—without a server or account.
Export the NotebookLM source pack, then clear the page. Refreshing or closing the tab also removes the current analysis.
See which job requirements have direct evidence, transferable evidence, weak proof, or no defensible support in your edited resume.
Prepare questions based on critical job demands, evidence gaps, interview stage, seniority, and selected interview formats.
Identify candidate stories and the Situation, Task, Action, Result, ownership, or metrics still missing before practice.
Download four lightweight Markdown or text files that keep the job, candidate evidence, interview plan, and NotebookLM instructions separate.
Create a private notebook, add the four generated sources, paste the custom coaching instruction, and follow the ordered prompt sequence. NotebookLM can then ground practice in your own job description and edited evidence rather than inventing candidate experience.
It does not predict hiring outcomes, provide live covert interview answers, or prove skills that are absent from the sources. Local matching is a preparation aid; review every requirement and candidate fact before use.
Use edited copies. Remove names, contact details, addresses, identification numbers, references, and confidential employer information before pasting or opening a file. Source text remains only in this tab until you clear, refresh, or close it.
No. Matching and report generation run in the current browser tab. The production edition accepts pasted text, TXT, and Markdown files only.
No. It summarizes document coverage, evidence quality, and STAR completeness. It cannot measure interviewer preferences or final performance.
It should not. Missing facts remain candidate-input questions so the notebook does not fabricate experience, ownership, or results.
This tool structures the evidence. NotebookLM provides source-grounded study, question practice, citations, and final briefing generation from those sources.
These details tailor the questions, risks, prompt sequence, and interview-day briefing.
Use edited copies with personal and confidential details already removed. Paste mode is recommended and uses no parser library.
This page analyzes the text in the current browser tab. It does not upload source text, create an account, or save a report.
No source text is being uploaded or saved.
Check resume-to-role fit and close gaps before you walk into the interview.
Open the Resume Matcher → Related guideUse the Grounded Research Loop to prep company, team, and role context.
Open the research workflow → Related toolBuild custom follow-up and negotiation prompts for your specific offer.
Open the Prompt Generator →Working across more than one AI tool? Explore Multi-AI Systems →
Learn what to upload, what to de-identify, and when sensitive work requires an approved organizational environment.