Enables resume review against job descriptions through a three-stage pipeline: match scoring, experience rewriting, and ATS optimization. Supports text or document uploads.
Enables AI agents to upload resumes and receive structured ATS scores with parseability, section coverage, contact-info, and keyword analysis, along with qualitative improvement suggestions via an LLM.
MCP server that scores a structured resume against a deterministic 4-category engineering rubric, providing numeric scores, evidence, bonus points, deductions, and improvement areas without an LLM call.
Enables AI assistants to tailor a resume to any job description by extracting keywords, analyzing gaps and ATS compliance, managing versions, and compiling PDF/LaTeX outputs entirely locally without external API keys.
Enables evidence-grounded resume tailoring by generating ATS-readable LaTeX/PDF resumes from a user-curated experience bank, with every bullet traceable to evidence and inferred wording flagged for user approval.