What is AI Job Search?
AI Job Search is an open-source Claude Code workflow for evaluating vacancies, tailoring CVs and cover letters, and preparing interview material. Your candidate profile, source documents and application history live in a project folder. The selected AI service still receives the context needed to perform its work.
The /setup, /scrape and /apply commands connect your recorded experience to vacancy discovery, fit evaluation and application drafting. A separate reviewer examines the drafts before the workflow compiles their PDFs and checks layout and extractable text. The resulting documents and their source files remain available for your own review.
This terminal-driven framework uses Python, Bun and a suitable LaTeX installation alongside the configured AI agent. Claude Code is the primary documented host. Some portal skills can work with other agents, but that does not establish equivalent support for the entire application workflow.
The checked release is version 1.7.3, published October 19, 2026, with MIT covering the framework itself. Model access and optional connected services have separate requirements. This profile reviews official source and documentation; it does not report an independent installation or a measured recruitment outcome.
Key capabilities
- A reusable candidate profile The setup workflow can use existing career documents, a pasted CV or a guided interview. It records experience and preferences for later applications. Read the generated profile before relying on it. An incomplete source document can otherwise become a persistent gap in every subsequent draft.
- Job portal searches The repository includes tools for Danish portals as well as LinkedIn public listings and Freehire. Results are deduplicated and presented for review. Coverage depends on the installed portal tools and their access conditions. A successful search does not establish complete coverage of a country or profession.
- Vacancy evaluation and ranking The apply workflow evaluates a posting against the candidate profile. The rank command can assess a larger batch before you choose one. Treat its fit assessment as an aid to reviewing requirements. It cannot know an employer's internal selection process or promise an interview.
- Tailored CVs and cover letters An agent drafts application documents from the profile and posting, then a reviewer supplies corrections. LaTeX produces the PDFs. The workflow checks page layout and extractable text, including supported keyword coverage. Those checks do not certify acceptance by every applicant tracking system.
- Interview preparation The interview workflow uses the archived posting, submitted documents and recorded feedback to prepare for a particular stage. It can build practice questions and a mock interview. Review company research and every suggested example against your actual experience before using it in a conversation.
- Application tracking and outcomes A local tracker and per-application archive retain the posting, submitted materials and outcome information. An HTML report offers an offline view of that record. Recording what actually happened is necessary for meaningful follow-up; generated status guesses should not replace confirmed correspondence.
- Optional connected workflows Documented commands can publish a pipeline view to Notion or examine Gmail for application status signals. These need their respective connectors and account permissions. The Gmail flow proposes changes for approval. Connected accounts introduce additional data processing beyond the local project directory.
- Posting integrity checks Version 1.7.3 documents a deterministic posting check and narrower permissions for skills and reviewing agents. The check flags several hidden-instruction patterns before drafting. The security policy explains the remaining boundaries. It explicitly does not describe a complete sandbox or a guarantee against manipulation.
Where AI Job Search fits
Preparing a technical job application
Start with an accurate record of projects, responsibilities and measurable work. Evaluate one real vacancy, then review the proposed CV and letter line by line. Keep statements that the underlying profile supports. Check that the final PDF names the correct company, role and contact information before submitting it yourself.
Managing a focused search
Use the search tools for the portals relevant to your market. Rank a bounded set of postings, inspect the stated gaps and choose the applications worth preparing. The shipped Danish search coverage is useful context for adoption. Another market may require a different portal skill or manual posting input.
Adapting documents for a particular role
Use the vacancy to decide which existing experience deserves space. The framework can reorganize and phrase supported material, but professional judgment still determines relevance. Inspect the extracted PDF text as well as its appearance. A visually attractive CV can still contain an incorrect link or a poor reading order.
Preparing for the next interview stage
Work from the exact CV and cover letter already sent to the employer. Add verified feedback from the previous round, then rehearse examples that demonstrate the requested skills. The archive helps maintain consistency. It should not become a source of invented achievements or scripted claims you cannot explain.
Keeping career information under control
Use a private working repository for real candidate information. The setup guide explains the distinction between contributing a public fork and maintaining a private copy. Review tracked files before pushing changes. A local folder can still be uploaded through Git or supplied to a connected model.
Reviews of AI Job Search
Be the first to share your experience with AI Job Search.
Write a review
Loading review form…
Alternatives to AI Job Search
AnatomyAnatomy is an MIT-licensed agent skill and Node drawing kit for interactive isometric figures, with SVG, HTML and React output, WebGL and a beta 3D mode.
Cloudflare Security Audit SkillMIT-licensed Cloudflare skill for coding agents that runs a six-phase source security audit with coverage tracking, independent verification and validators.