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How to prepare a stage-specific interview pack with AI Job Search

Build a prep pack and mock interview for a scheduled interview on a tracked application.

Who it is forA candidate with an interview booked for a tracked application who needs to prepare quickly and accurately.

The problemInterview prep is slow when the posting, the submitted CV and the company research are spread across different places.

The outcomeA stage-specific prep pack with likely questions mapped to your STAR examples, verified company research and an offered mock interview.

What you need first

  • Claude Code (Pro, Max, Team subscription or Anthropic API credits)
  • Python 3.10+
  • Bun
  • A LaTeX distribution with lualatex and xelatex
  • git and the gh CLI to fork the repo
  • Your CV, past applications and other career documents to load into /setup

Steps

  1. gh repo fork MadsLorentzen/ai-job-search --clone
  2. python3 tools/install_portal_clis.py
  3. Run claude inside the repo and make sure the application is tracked from an earlier /apply.
  4. Run /interview and name the tracked application when asked.
  5. Work through the question map, then accept the offered mock interview and check that the bridge answers stay honest about gaps.

Prompt for your agent

In the ai-job-search repo, run /interview for the tracked application <application name>. Expect a prep pack built from the archived posting, CV and cover letter, with likely questions mapped to STAR examples. Verify that no experience appears in an answer that is not in your archived documents.

Caveat. Interview prep depends on the application being tracked first, so run /apply or record it with /outcome before using /interview.

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