AI Job Search Explained: A Local Workflow for Applications and Interviews

CODE LAB · PROJECT SPOTLIGHT

AI Job Search TypeScript · MIT

Explore AI Job Search’s application workflow, portal integrations and actual TypeScript source, with privacy and factual-review considerations.

GitHub source ↗Releases & builds ↗

Preview: ai-job-search-dev/ai-job-search on GitHub

Job applications involve repeated work: comparing a role with your experience, selecting relevant examples and drafting a clear application. AI Job Search organizes that work as a Claude Code-based framework with a candidate profile and reusable commands.

The project documents role evaluation, tailored CVs, cover letters and interview preparation. Its repository includes portal integrations and a drafting-and-review workflow. The project has moved from an individual-owner address to an organization; use the current canonical repository when following installation instructions and checking releases.

This source-and-documentation review was checked November 13, 2026. Project-supplied images and reported results are attributed below; no new hands-on benchmark is claimed.

What does AI Job Search do?

Begin with a factual candidate profile and a real job posting. Ask the framework to identify the match, the missing requirements and the evidence supporting each proposed claim. Review the draft against your actual experience before sending anything. The application should remain accurate even when the system finds an attractive way to phrase a skill or project.

Inside the source: normalize a portal’s base URL

This helper reads a configurable Freehire API base URL, trims whitespace, falls back to a default and removes trailing slashes. It illustrates how one portal integration prepares a service address. It does not prove that every job board is supported, nor does it demonstrate a successful search on a Korean recruitment site.

10export function baseUrl(): string {11  const raw = (process.env.FREEHIRE_API_URL ?? "").trim()12  return (raw || DEFAULT_BASE_URL).replace(/\/+$/, "")13}

Source: ai-job-search-dev/ai-job-search at 0d0d1a9. License: MIT. Original lines retained; syntax colors and line numbers added for this article.

MIT License

Copyright (c) 2026 Mads Lorentzen

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

Getting started with a bounded task

Follow the current setup guide for the host agent and portal skills you intend to use. Review which files hold your profile, application history and generated documents. Check repository visibility and ignore rules before committing personal information. Test one supported source and inspect the extracted posting before relying on it to produce application materials.

Limits and what to verify

A match score is an aid to prioritization, not an employer’s decision. Listings can expire, portals can change and model-written claims can overstate experience. Check dates, links and facts manually. API availability and portal-specific permissions vary. The maintainer’s personal job-search story is a reported experience, not a promise of interviews or employment.

Where it fits in your workflow

AI Job Search is most useful as an organized drafting and review workflow under your control. Keep factual evidence attached to each claim and make the final submission yourself. The public repository and setup documentation provide the best starting point for evaluating supported integrations.

Related Code Lab: T3 Code and AI coding-agent interfaces. For the source-review format used here, see our Lichii repository walkthrough.

Official references: Repository · README at reviewed revision · Release history · Source excerpt.