The job search that runs on your machine. AI job application framework built on Claude Code: evaluate postings, tailor CVs, write cover letters, prep interviews. Fork it and own it.
You are helping the user build a job-portal search skill for a job board in their market. The repo ships worked examples of the pattern (four Danish portals plus the country-agnostic linkedin-search and freehire-search), and the README invites users elsewhere to build equivalents — this command turns that invitation…
You are helping the user register their own CV or cover letter template with the AI Job Search framework — LaTeX, Typst, or any other toolchain that compiles to PDF from the command line. The framework ships with moderncv (banking style) for CVs and a custom cover.cls for cover letters. This command lets the user swap…
You are enriching the candidate profile by discovering competencies hidden in documents and public online presence. This command is additive only — it never modifies existing profile content, only extends it.
You are scanning the user's Gmail for status signals on tracked job applications (interview invites, assessment links, offers, rejections) and, once approved, writing the detected changes into jobsearchtracker.csv and documents/applications/ /outcome.md - the same two places /outcome writes to, in the same schema.
Generate a self-contained HTML dashboard from jobsearchtracker.csv and the application archives under documents/applications/. The output is a single .html file — no server, no dependencies — that can be opened directly in a browser.
You are preparing the user for a real, scheduled interview on one of their applications. The frameworks for this already exist - 07-interview-prep.md (STAR examples, tough questions, questions to ask, roleplay protocol) and the Company Research Checklist in 04-job-evaluation.md - and the /outcome archive records which…
You are publishing a read-only view of the job search into the user's Notion workspace: one database row per job, with a detailed page per shortlisted match. The repo files stay the system of record - jobscraper/seenjobs.json owns scraped/ranked jobs and jobsearchtracker.csv owns applications. Notion is a disposable…
You are recording what happened to a job application: progress updates (interview invitations, stages completed, offers) and final resolutions (hired, rejected, no response). The data lands in two places the framework already reads but nothing systematically writes.
You are batch-scoring the jobs that /scrape has collected, so the user can decide where to spend /apply effort. /scrape finds and dedupes postings; /apply evaluates one at a time in depth. /rank is the bridge: it scores every new posting against the fit framework and returns a ranked shortlist.
You are running the onboarding setup for the AI Job Search framework. Your goal is to collect the user's professional information and populate all profile files so the /apply workflow works out of the box.