suraj-davariya-ai-job-search

CareerForge

An AI job-search assistant that finds postings, writes tailored CVs and cover letters, and compiles them to print-ready PDFs — all on your own machine.

🌍 Read this in your language (alphabetical · 12 available · machine-translated, English is canonical):

العربية (Arabic) · বাংলা (Bengali) · 简体中文 (Chinese, Simplified) · Deutsch (German) · English · Español (Spanish) · Français (French) · हिन्दी (Hindi) · Bahasa Indonesia (Indonesian) · 日本語 (Japanese) · Português BR (Portuguese) · Русский (Russian)

Planned (help translate — i18n/CONTRIBUTING.md): Chinese (Traditional), Dutch, Filipino, Hebrew, Italian, Korean, Malay, Marathi, Persian, Polish, Portuguese (Portugal), Romanian, Swahili, Tamil, Telugu, Thai, Turkish, Ukrainian, Urdu, Vietnamese.

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New here? Start with the guide. The friendliest way to understand CareerForge is the documentation site — Quick Start, all three commands, the dashboard with live demos, privacy, and FAQ. No programming needed to read it.

• 🌐 Read it now: suraj-davariya.github.io/ai-job-search — hosted, nothing to install.
• 📊 Click through the dashboard: suraj-davariya.github.io/ai-job-search/dashboard — the real UI on fictional sample data, read-only.
• 💻 Prefer local? Run npm run dev inside docs-site/ (or see its README for the one-command static build).

What is this?

CareerForge is a job-search toolkit you run inside Claude Code — an AI assistant that lives in your terminal. You type commands and plain-English prompts; the AI does the work. No programming knowledge required.

Here is what it can do for you today:

Step	You say	What happens
1. Build your profile	/setup	Claude reads your existing CV, LinkedIn export, diplomas, or interviews you — then writes your candidate profile
2. Find new jobs	/search	Claude searches your configured job portals, deduplicates against jobs you've already seen, scores each one for fit, and shows you a ranked table
3. Apply	/apply <url or paste>	Claude scores your fit, tailors your CV, writes a cover letter in the posting's language, has a second AI reviewer critique both, applies the edits, compiles two PDFs, and runs a final verification checklist

Your data never leaves your machine. Your profile, CVs, cover letters, and application log are all stored locally and are never committed to git.

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How it works — the 3-minute version

Your documents                  CareerForge                     Output
─────────────    ──────────────────────────────────────    ──────────────
  CV / LinkedIn  →  /setup  →  Candidate profile           Profile files
                                    ↓
  Job portals    →  /search →  Ranked job list              Console table
  (configured)           ↓
                      Pick a job
                           ↓
  Job posting    →  /apply  →  Fit score & verdict
                               Tailored CV  (2 pages)  →  cv/main_<co>.pdf
                               Cover letter (1 page)   →  cover_letters/cover_<co>.pdf
                               Reviewer critique
                               Revision pass
                               Verification checklist

What CareerForge does not do:

• Submit applications on your behalf (you review and send)
• Invent skills or experience you don't have
• Upload anything to the cloud

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What you need

1. Claude Code

Claude Code is the AI assistant that runs CareerForge. Install it once:

npm install -g @anthropic-ai/claude-code

Then log in:

claude

Claude Code requires an Anthropic account. The Free and Pro plans both work; Pro is recommended for heavy usage.

Not sure what Claude Code is? Think of it as a smart terminal assistant that can read files, search the web, and run commands — guided by the CareerForge instructions.

2. LaTeX (for PDF generation)

CareerForge compiles your CV and cover letter to PDF using LaTeX. Two compilers are needed:

Compiler	Used for	Why
lualatex	CV	Required by the fontawesome and lato packages
xelatex	Cover letter	Required by fontspec for bundled fonts

macOS (recommended — installs both compilers):

brew install --cask mactex

Or download from tug.org/mactex.

After installing, add the extra CV packages:

sudo tlmgr install fontawesome lato tcolorbox dashrule enumitem multirow \
                   ifmtarg fontaxes mweights pgfopts

Linux (TeX Live):

sudo apt-get install texlive-full   # Debian/Ubuntu

Windows: Install MiKTeX — it fetches missing packages automatically.

3. Python 3.10+ (optional — for salary benchmarking)

python3 --version    # must be 3.10+
pip install openpyxl # only needed if importing salary data from Excel

4. pandoc & poppler (optional — for ATS-safe CV exports)

pandoc --version     # generates the .docx export (and higher-fidelity .txt)
pdftotext -v         # poppler — runs the ATS parse self-check

Without these, /apply still produces the polished PDF and a plain-text .txt; only the .docx export and the PDF parse-check are skipped (graceful degradation).

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Quick Start

# 1. Clone the repo
git clone https://github.com/suraj-davariya/ai-job-search.git
cd ai-job-search

# 2. Open CareerForge in Claude Code
claude

# 3. Build your profile (answer Claude's questions or point it at your documents)
/setup

# 4. Search for jobs
/search

# 5. Apply to one
/apply https://company.com/jobs/your-role

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Commands in depth

/setup — Build your candidate profile

Populates seven profile files from your real data. Claude asks questions or reads your documents — no typing if you have files.

Three onboarding paths:

Path	When to use
A — Scan documents	You have CVs, a LinkedIn export, diplomas, or reference letters in the documents/ folder
B — Import a CV	You have a single clean CV and want a fast start
C — Live interview	Starting fresh; Claude interviews you

Example prompts:

/setup

/setup --section search

(Jumps straight to updating your target job portals and location preferences without re-running the full interview.)

/setup --section experience

(Updates just your work history — useful after a job change.)

What gets built:

File	Contents
01-candidate-profile.md	Identity, education, work history, skills, projects
02-behavioral-profile.md	Working style, culture preferences, motivations
03-writing-style.md	(static framework — no personal data)
04-job-evaluation.md	Your strong/weak areas, career goals
05-cv-templates.md	Profile statements per role type
06-cover-letter-templates.md	(static templates)
07-interview-prep.md	STAR stories from your experience
search-queries.md	Your target job portals, queries, location tiers

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/search — Find new job postings

Searches your configured job portals via web search, deduplicates against jobs you've already seen, assigns a fit signal (High / Medium / Low), and presents a ranked table. When you pick a number, the job is handed straight to /apply.

Arguments:

Syntax	Behaviour
/search	Runs your top 3 priority query categories
/search data science	Prioritises categories matching "data science"
/search broad	Runs all configured query categories

Example prompts:

/search

/search machine learning

/search broad

Example output:

Found 7 new positions (2 high, 3 medium, 2 low match)

 #  Fit     Title                    Company        Location        Deadline   URL
 1  High    Senior Data Engineer     Acme Corp      Amsterdam, NL   2026-06-20  …
 2  High    ML Platform Engineer     Beta Labs      Remote (EU)     Open        …
 3  Medium  Data Analyst             Gamma AG       Berlin, DE      2026-06-15  …
…

Want me to evaluate any of these in detail? Just give me the number(s).

All portals come from your config. Nothing is hardcoded — add any job board (LinkedIn, Indeed, Jobindex, Stepstone, etc.) to search-queries.md and it is automatically included.

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/apply — Produce a tailored CV and cover letter

Takes a job URL or pasted description and runs the full application pipeline: