deepread-resume-parserlisted

# DeepRead Resume Parser Turn any resume or CV — PDF, scanned, or wildly creative two-column design — into clean, structured JSON: contact details, work history with dates and titles, education, skills, and computed years of experience. Each field carries a `needs_review` flag, so your ATS ingests the confident fields and routes only the ambiguous ones to a recruiter. > This skill instructs the agent to POST documents to `https://api.deepread.tech` and poll for results. No system files are modified. ## Why resumes break normal parsers Resumes have no standard layout: two columns, sidebars, icons, tables, graphics, dates as "Jan 2021 – Present." Regex/template parsers shatter on the first creative design. DeepRead reads the document the way a human does — visual + semantic — runs **multi-model consensus**, and flags low-confidence fields instead of silently mangling a job title. ## What You Get Back ```json { "schema_version": "dp02", "status": "completed", "extraction": { "fields": [ {"key": "full_name", "value": "Priya Nair", "needs_review": false, "location": {"page": 1}}, {"key": "email", "value": "priya.nair@email.com", "needs_review": false, "location": {"page": 1}}, {"key": "phone", "value": "+1 415 555 0148", "needs_review": false, "location": {"page": 1}}, {"key": "years_experience", "value": 7, "needs_review": true, "review_reason": "Computed from overlapping roles", "location": {"page": 1}}, {"key": "work_history", "valu