Free ATS Resume Checker

How it works

1. You apply on an employer-specific Workday portal. Each company runs its own Workday careers site, typically with its own account signup. Your profile generally doesn't carry over between employers, which is why the process feels repetitive.
2. Your resume is parsed into structured fields. After you upload a resume, Workday typically pre-fills structured fields — work history, education, skills — from it, and shows you the result for review before you submit. What lands in those fields is what the employer's recruiting team works with.
3. You answer screening ("knockout") questions. Employers commonly configure yes/no or numeric questions — work authorization, required years of experience, certifications. Based on how employers use these across systems, disqualifying answers here are a far more common cause of fast rejections than anything about your resume's wording.
4. Recruiters review inside Workday's tools. From there, the employer's recruiters typically work through applicants using Workday's review and search tools. How any given company screens, filters, or prioritizes is their configuration and process — not something Workday publishes or standardizes.

Myths vs. reality

• Myth: “Workday gives your resume a score and auto-rejects you below a cutoff.” Workday doesn't publish any such mechanism, and rejection behavior varies by employer configuration. The fast automated rejections candidates experience typically trace to knockout question answers — a "no" on work authorization or required experience — not to a secret resume score.
• Myth: “Hiding extra keywords in white text will boost you through Workday.” Because Workday parses your resume into structured fields that you (and recruiters) can see, stuffed text either lands visibly in those fields or gets you flagged by an actual human reading the application. It's a risk with no verified upside.
• Myth: “If you weren't rejected instantly, a human read your resume.” Not necessarily — review timing is up to each employer's recruiting team. A quiet week typically means your application is sitting in a queue, not that it passed or failed anything.

What you can control

• Review and fix the parsed fields. The parsed work-history and education fields are typically what recruiters work from — if parsing garbled your titles or dates, edit them manually before submitting rather than resubmitting the file.
• Answer knockout questions exactly and honestly. Read numeric questions literally ("5+ years of X") and answer what's true. These questions are the most commonly configured hard filter — and misstating them to pass catches up with you at the interview or offer stage.
• Keep the resume format parser-friendly. Simple headings, standard section names, no tables or text boxes. The cleaner the structure, the more accurately your history lands in Workday's fields.
• Still tailor the attached resume. Recruiters typically can open the original file. Keyword alignment with the job description matters for their search and skim — tailor it per posting like you would anywhere else.
• Budget time for the form. Workday applications are longer than most. Rushing the re-typed fields is how errors creep into exactly the data recruiters filter on.

How it works

1. You fill a short application form on the company's job page. Greenhouse applications are typically a single page: contact fields, a resume upload, and whatever custom questions the employer added. No account creation, unlike the big-enterprise systems.
2. Your resume may pre-fill some fields. Uploading a resume commonly auto-fills contact and basic fields from it. The original file stays attached to your application, and it's what reviewers typically open.
3. Custom application questions go to human readers. Those "Why do you want to work here?" or role-specific questions are configured by the hiring team and read by them — they're commonly used to gauge specificity and effort, not parsed for keywords.
4. The hiring team reviews in a pipeline. Recruiters and hiring managers typically move candidates through stages (application review, screen, interviews) with scorecards. Speed and criteria are the team's own process; Greenhouse structures it rather than deciding it.

Myths vs. reality

• Myth: “Greenhouse scores your resume and rejects you before any human sees it.” Greenhouse is a recruiter-workflow product — pipelines, scorecards, interview kits. It doesn't market or publish any resume auto-scoring or auto-rejection capability, and applications land in a queue for the hiring team's review. If you were rejected quickly, the likeliest explanations are an unusually responsive team, a screening-question mismatch, or volume — not a robot verdict.
• Myth: “You need to hit a keyword-match percentage to pass Greenhouse.” There's no published match-score gate to pass. Keywords still matter for a human reason: recruiters skim and search for the posting's terms when reviewing at volume — which is worth optimizing for regardless of which system is involved.
• Myth: “The custom questions are just keyword filters — paste your resume summary.” Hiring teams commonly weight those answers precisely because they're read by people. A pasted generic answer typically hurts more with humans than it could ever help with software.

What you can control

• Make the attached file the best version. Reviewers typically open your actual resume file. A clean, tailored PDF that parses well covers both the pre-fill and the human read.
• Mirror the posting's keywords for the recruiter skim. Not for an algorithm — for the person reviewing dozens of applications who searches and scans for the job description's terms.
• Answer custom questions specifically. Two or three concrete sentences referencing the actual company and role commonly beat a polished generic paragraph. These answers are read.
• Check the auto-filled contact fields. Pre-fill from your resume is convenient but not perfect — a garbled phone number or email in the form fields is an unforced error.
• Apply once, well. Duplicate applications to the same posting land in the same pipeline and read as noise to the team reviewing them.

How it works

1. You apply on a short hosted form. Lever postings typically live at a jobs.lever.co URL with a brief form: resume upload, contact fields, links, and any custom questions the employer added. No account required.
2. Basic details are read from your resume. Your upload commonly pre-fills contact fields, and the original file stays attached for reviewers to open. Clean parsing means fewer errors in what the team sees first.
3. Your application becomes a candidate record. Inside Lever, the team works with candidate profiles they can tag, search, and move through pipeline stages — a relationship-management model where recruiters drive the actions.
4. Humans move you forward (or not). Advancing, archiving, and messaging are done by the recruiting team per their own process. Lever structures the workflow; the judgment calls are the employer's.

Myths vs. reality

• Myth: “Lever ranks applicants with an AI score and auto-rejects the bottom.” Lever doesn't market or publish any resume auto-scoring or auto-rejection mechanism — its product is pipeline and relationship management for recruiting teams. Your application typically waits for human review; how fast and how strict that review is depends on the team, not the software.
• Myth: “Formatting tricks can game Lever's parser into promoting you.” Based on the candidate-visible flow, parsing in Lever mainly pre-fills fields and makes your record searchable. There's nothing published to "game" — but a resume that parses cleanly does avoid garbled contact details and makes the JD's terms findable when a recruiter searches, which is the practical win.
• Myth: “If the posting is on Lever, cover letters and questions are ignored.” What gets read is the hiring team's choice, and teams that add custom questions commonly do read them. Skipping or phoning in an optional field is a visible signal to a human, not a neutral omission.

What you can control

• Use the JD's vocabulary in your resume. Recruiters commonly search and skim candidate records for the posting's terms. Mirroring the job description's wording (where true for you) is what makes you findable.
• Keep the resume format simple. Standard sections, no tables or graphics — so pre-filled fields come out right and the attached file reads cleanly for humans.
• Fill the links fields. Lever forms typically ask for LinkedIn, GitHub, or portfolio links — for many teams that's the second thing opened after the resume. Working links, current content.
• Answer custom questions like a human wrote them. Because one did. Short, specific, role-aware answers beat generic paragraphs.
• One application per role. Your application is a persistent record on the team's side — duplicates don't create a second chance, just clutter under your name.

How it works

1. You create an account on the employer's Taleo portal. Taleo applications typically start with an employer-specific account and a multi-step form flow — it's the longest application experience of the major systems.
2. Your resume is parsed into form fields — imperfectly. Taleo commonly pre-fills work history and education from your upload. Its parsing is older-generation, so complex layouts frequently come through garbled — and you're typically shown the fields to review and correct.
3. You answer screening questionnaires. Employers commonly configure knockout questions (work authorization, minimum experience, certifications, willingness to relocate). Disqualifying answers are the classic source of fast automated rejections in enterprise hiring.
4. Recruiters search and filter the applicant pool. Recruiters commonly work Taleo's applicant lists with keyword and field searches against the requisition's terms — which is why resumes that mirror the posting's exact vocabulary get surfaced and generic ones don't.

Myths vs. reality

• Myth: “Taleo auto-rejects 75% of resumes before a human sees them.” That statistic circulates endlessly with no published source — Oracle doesn't publish rejection rates, and no verified documentation supports a built-in resume-scoring cutoff. The real, verifiable filters in Taleo-style flows are knockout questionnaire answers and recruiters' own keyword searches. Those are worth optimizing for; the 75% robot is folklore.
• Myth: “Taleo only reads the top third of your resume.” There's no published basis for this. Parsing quality does vary with formatting — which is a reason to use simple, standard layouts throughout — but "only the top third counts" is superstition, not documentation.
• Myth: “Older system means keyword stuffing still works.” The parsed fields and the attached resume are both visible to the recruiters doing the searching. Stuffing reads as spam to exactly the person you're trying to reach; mirroring the requisition's real terms where they're true for you is the legitimate version.

What you can control

• Correct every parsed field. Assume Taleo's parsing got something wrong and review the pre-filled work history line by line. Recruiters filter on those fields — garbled dates or titles are silent disqualifiers.
• Mirror the requisition's keywords. Recruiter keyword search is the real "algorithm" in Taleo workflows. Use the posting's exact terms — spelled-out and abbreviated forms both — where they honestly describe your experience.
• Answer knockouts literally. Numeric and yes/no questionnaire answers are the most common hard filter. Read them precisely, answer truthfully, and don't leave "optional" qualification fields blank if you qualify.
• Strip the fancy formatting. Tables, text boxes, columns, and graphics are what older parsers most often garble. For Taleo employers especially, a plain single-column resume is the safe format.
• Finish the whole form. Taleo applications are long on purpose-built detail. Abandoned or half-filled sections mean missing data in the fields recruiters search — complete beats clever.
• Keep a plain-text master copy. Re-typing into Taleo portals is a fact of life. A plain-text version of your resume makes the copy-paste rounds faster and cleaner.