CareerCAN I VIBECODE
Jobscan?
BUILD FIRST
- One specific customer type and one primary use case
- A vertical slice that completes the main job without manual workarounds
- Visible limits, review steps, and a fallback when an external dependency fails
LEAVE FOR LATER
- Broad third-party integrations
- High-scale collaboration, syncing, and permissions
- Automation that can cause harm without human review
RESEARCH NOTES
What this tool actually does.
Jobscan (jobscan.co) is a career/resume optimization SaaS for job seekers. Core loop: paste or upload a resume (Word, PDF, or LinkedIn import) plus a target job description, then scan to get a Match Score (percentage) estimating alignment with the posting. The scanner runs 30+ checks and produces a Match Report surfacing missing keywords, hard-skill vs soft-skill gaps, and ATS issues (file type, professional file name, verb tenses, plurals, abbreviations, layout, tone, measurable results). AI Optimize (formerly One-Click Optimize) is an AI editor that compares the resume to the job description and match report, generating in-context suggestions across four lenses (skills, searchability, ATS, human recruiter) that users accept, reject, or edit; match score updates in real time, with a before/after compare mode and PDF/DOCX download. It also offers an AI Resume Builder with an interview-st
RESEARCHED BUILD PROMPT
Give this to your coding agent.
Build a focused replacement for the Jobscan resume-optimization workflow (do NOT copy Jobscan's brand, logo, copy, or UI). Core loop: a user pastes or uploads a resume (plain text, PDF, or DOCX) and pastes a target job description; the app returns a Match Score (0-100%) plus a Match Report. Implement a keyword-matching engine that tokenizes both texts, extracts job-description keywords (skills, tools, certifications, action verbs), and reports which are present vs missing, flagging hard-skill vs soft-skill gaps and basic ATS issues (verb tense, plurals, abbreviations, file name, section headers). Add an AI Optimize mode: an LLM (e.g., OpenAI-compatible API) generates in-context rewrite suggestions for weak bullets/sections; each suggestion is shown as an accept/reject/edit card, and the Match Score recomputes in real time after each change. Include a before/after side-by-side compare and export of the tailored resume as PDF/DOCX. Add an optional AI Resume Coach: a guided one-question-at-a-time chat that turns experience into achievement bullets. Tech: React or Next.js front end, a Node/Python API, a keyword-scoring module, and an LLM integration with a settings page for API key/model. Out of scope: job-board search, auto-apply/auto-fill, account billing, multi-user collaboration, and any Jobscan branding/assets. Deliver a README covering setup, env vars, how the scoring algorithm works, rate-limit/API-cost caveats, and the limitation that match scores are heuristic estimates, not guarantees of ATS or recruiter outcomes.