Welcome, busybees
Most people using AI for job search are stuck in a loop: open a chat window, paste a job description, paste a resume, ask for a rewrite, copy the output, close the window, lose everything, and start from scratch tomorrow for the next role.
That’s not a system. That’s a treadmill.
Claude Code... Anthropic’s terminal-based agent... changes this completely.
Instead of chatting, you build a persistent, file-based job search system on your own machine: your resume, your applications, your interview prep, your research, your follow-ups, all living in one folder, versioned with git, orchestrated by Claude.
This is what engineers have quietly been doing for months. Today I’ll show you how to build it.
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The Mental Model: Your Job Search as a Codebase
Think of your job search the way a developer thinks about a project:
A repo (your job-search/ folder) holds everything
Configuration (CLAUDE.md) teaches Claude your background, voice, and preferences, once
Skills are reusable workflows (tailor a resume, draft a cover letter, research a company)
Subagents do specialized heavy-lifting (a “company researcher,” an “interview coach”)
Slash commands are one-keystroke triggers for common tasks
Hooks enforce quality gates (never submit a resume with a typo, never apply without logging it)
MCP servers connect Claude Code to Gmail, your calendar, LinkedIn exports, your Notion job tracker
Once set up, applying to a role goes from 90 minutes of copy-paste to a single command: /apply <job-url>.
Layer 1: The Foundation, CLAUDE.md
This is a markdown file in your job search folder that Claude Code reads every session. It’s your permanent context so you never have to re-explain yourself.
What to put in it...
My Job Search Context:
About Me:
7 years in product management, last 3 years in fintech
Based in USA, open to remote work
Target roles: Senior PM, Principal PM
Compensation target: $180K–$220K base
My Voice:
Direct, no fluff, no buzzwords like “synergy” or “leverage”
I write in active voice, short sentences
I quantify outcomes wherever possible
Resume Rules:
Never fabricate metrics
Never exceed 2 pages
Lead every bullet with a verb, not a noun
Flag any gap between my experience and the JD
Application Rules:
Log every application in applications.csv
Never submit without my explicit approval
Always save the JD as a dated markdown file
Once this exists, every interaction inherits it. No more “as I mentioned last time…”
Layer 2: Skills, Your Reusable Workflows
Skills are markdown files that teach Claude repeatable procedures. Drop them in .claude/skills/ and Claude auto-invokes the right one based on what you ask.
High-value skills to build:
resume-tailor: takes a JD and produces a tailored version of your resume, flagging fabricated claims
cover-letter: drafts a cover letter using your voice rules, with a non-boilerplate opening
jd-analyzer: breaks a job description into must-haves, nice-to-haves, and hidden red flags (unrealistic scope, vague comp, serial reorgs)
star-builder: turns your raw work stories into polished STAR-format interview answers
negotiation-coach: prepares counter-offer language and rebuttals for common recruiter pushbacks
You write each skill once. It works forever, across every role you apply to.
Layer 3: Subagents, Specialized Workers
Subagents run in isolated contexts, which matters because deep research can pollute your main session. Give them narrow, well-defined jobs.
The three subagents worth building first:
company-researcher Reads a company’s website, recent news, Glassdoor reviews, and leadership background. Outputs a one-page briefing: strategic challenges, culture signals, and 5 sharp questions to ask in your interview.
interview-simulator Role-plays as the hiring manager for a specific role. Asks one question at a time, waits for your answer, then critiques it using the STAR method before moving on. Stays in character until you say “break.”
application-tracker Reads your applications.csv, tells you which companies haven’t responded in 10+ days, drafts follow-up emails, and flags roles where you should stop waiting.
Layer 4: Slash Commands, One-Keystroke Triggers
This is where the system starts to feel like magic. You define commands like:
/apply <url>: fetches the JD, analyzes it, tailors your resume, drafts the cover letter, logs the application, and queues it for your review
/prep <company>: spins up the company-researcher subagent and outputs your interview briefing
/mock <role>: launches the interview-simulator for a specific role
/followup: scans your tracker and drafts all pending follow-up emails at once
/weekly: generates your Sunday-night job search report: applications sent, responses received, interviews booked, action items for the week
Each command is a markdown file that orchestrates your skills and subagents. Write it once, use it forever.
Layer 5: Hooks & MCP, The Safety Net and the Outside World
Hooks are scripts that fire automatically on events. Use them for quality gates:
Before any resume file is written → run a spell-checker, block the save if there are typos
After every application is logged → commit the change to git, so you have a full audit trail
On session end → append a summary to daily-log.md
MCP servers connect Claude Code to external tools. The high-leverage ones for job search:
Gmail MCP → Claude can read recruiter emails, draft replies in your voice, and surface messages you’ve missed
Google Calendar MCP → Claude checks your availability before proposing interview times
Google Drive MCP → Your resume master file lives in Drive; Claude pulls the latest version automatically
This is where “AI assistant” stops feeling like a novelty and starts feeling like infrastructure.
What a Real Workflow Looks Like?
You see a Senior PM role posted on LinkedIn. Here’s what happens:
cd ~/job-search
claude> /apply https://company.com/careers/senior-pm-123In the next 90 seconds, Claude Code:
Fetches the JD and saves it to applications/2026-04-23-company-senior-pm.md
Runs the jd-analyzer skill → flags that “10+ years experience” is aspirational and you’re a fit
Runs the resume-tailor skill → produces a tailored PDF in the application folder
Runs the cover-letter skill → drafts a 250-word letter with a hook tied to the company’s recent Series C
Logs the application as PENDING_REVIEW in applications.csv
Prints a summary for you to review before anything gets sent
You read it, make two edits, approve, and move on with your life.
The next morning, you run /weekly and see: 7 applications sent, 2 responses, 1 interview booked for Thursday. Claude has already drafted the prep brief for that interview and put it in your inbox.
That’s the operating system
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