Hireability

Feature tested: Clean Single-Column Resume

Result: Passed (7/10)

Verdict: Extracts almost all fields correctly on clean input — name split is the only notable artifact

Expected behavior: We uploaded a standard single-column PDF resume with clean formatting and clearly defined sections. The question was whether field extraction goes beyond the basics — and whether the name field, which appears straightforward on the resume, comes back the way you would expect. Check the JSON output closely, particularly the GivenName and FamilyName fields, and then look at what the competency entries actually contain for each extracted skill.

Why it matters / Conclusion: Clean resumes are where parsers are supposed to be flawless — and Hireability mostly is. But there is something in the name field that will catch you off guard when you see it, and once you find it the cause becomes clear from the raw TextResume field. There is also something in the skill competency output worth paying attention to — Hireability extracted 29 skills, but what it assigned to every single one of them is identical.

Feature tested: Multi-Column Resume Parsing — Two Column PDF

Result: Passed

Verdict: Full document misclassification — parser returned a Job Order structure instead of a Resume, all key fields empty

Expected behavior: We uploaded a two-column resume where personal details and contact information sit in the left column and experience, education, and certifications sit on the right. The question was whether the parser reads both columns correctly or treats the document as something else entirely. Open the JSON output and find the document type field first — then look for the candidate's name, email, and phone number.

Why it matters / Conclusion: This is where Hireability's most critical failure occurs — and it is not a missed field. The parser misclassified the entire document as a Job Order instead of a Resume. Once you see the output structure, you will understand immediately why name, email, phone, work history, education, and certifications all came back empty. The raw TextResume shows the PDF was read correctly — the breakdown is entirely in document classification.

Feature tested: Messy Resume Parsing — No Section Headers

Result: Passed (7/10)

Verdict: Strong recovery on messy input — certifications block and second work experience entry had notable errors

Expected behavior: We uploaded a resume with no clear section headers, inconsistent formatting throughout, and a skills list buried inside running text. The question was how much structured data Hireability could recover when the input gives it almost nothing to work with. Check the second work experience entry in the JSON output — specifically the employer name field — and compare it against what the resume actually shows. Then find the certifications block and see how many distinct entries came back.

Why it matters / Conclusion: This is the input that breaks most parsers — and Hireability recovers more than expected. Name, contact details, location, objective, education, first work experience, 15 skills, and hobbies all came back correctly. But there is one field in the second work experience entry carrying a value that looks reasonable until you check the input and see exactly where the parser went wrong. And the certifications block is worth opening carefully — what came back is not what was in the resume, and the reason why is visible in the formatting.