Job Search Assistant Plus

Problem

Job seekers often get stuck between resume drafting, job filtering, and interview prep. A resume may contain the right facts but bury priorities; job lists can be large without clear matching; target companies may still lack salary context, JD analysis, or skill-gap assessment. @user_ba7c4de9/job-search-assistant-plus turns this into a reproducible workflow: start from an existing resume or form data, produce multiple resume versions, generate a job recommendation report, tailor application versions, and prepare interview practice.

Core Workflow

• Resume intake and parsing: collect data through an HTML form when no resume exists, or parse PDF/DOCX files, including OCR when needed, into structured JSON with raw_text.
• Multi-version resume generation: render HTML using classic, modern, or sidebar templates and export PDF with Playwright; iterate using STAR, quantified outcomes, or JD keywords.
• Job recommendations: extract city, skills, and target roles from the resume, query the configured online spreadsheet via Tencent Docs MCP, score matches by location, role, skills, and company/industry, then produce an HTML report.
• Application tailoring: reorder projects and skills, rewrite experience bullets, self-evaluation, and job intention for each target role, then output separate PDFs with change notes.
• Career guidance and mock interviews: analyze the target company, role, salary range, skill gaps, and run scored interview practice.

Boundaries

It is best suited to campus or spring recruitment searches backed by the specified Tencent Docs spreadsheet and to users who need several resume variants quickly. Confirm the Tencent Docs connection and remove stale local files such as resume_form_data.json and matched_jobs.json before running. The job pool comes from the configured sheet rather than the full job market, and all resume edits should stay grounded in real experience rather than invented projects or inflated claims.