he-yufeng

FindJobs Agent — AI skill for Claude Code

AI community

LLM-powered toolkit for skill analysis, AI interviews, resume scoring, and job structuring.

How to install FindJobs Agent

This entry records only its repository, not the path inside it, so there is no exact command to give. Open he-yufeng/FindJobs-Agent and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What FindJobs Agent does

LLM-powered toolkit for skill analysis, AI interviews, resume scoring, and job structuring. Automates professional skill taxonomy and interview processes with adaptive difficulty.

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README

[![Python 3.10+](https://img.shields.io/badge/Python-3.10+-blue.svg)](https://www.python.org/downloads/) [![PyPI](https://img.shields.io/pypi/v/findjobs-agent.svg)](https://pypi.org/project/findjobs-agent/) [![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](LICENSE) [![CI](https://github.com/he-yufeng/FindJobs-Agent/actions/workflows/ci.yml/badge.svg)](https://github.com/he-yufeng/FindJobs-Agent/actions/workflows/ci.yml)

**[English](README.md) · [中文](README_CN.md)** · [Demo](#try-it-in-2-minutes-demo-mode) · [Quick Start](#quick-start) · [How It Works](#how-it-works) · [Features](#features)

What is FindJobs-Agent?

A full-stack job search assistant that crawls postings from major tech companies, analyzes them with LLMs, parses your resume, and runs AI mock interviews — so you can focus on preparing, not sifting through job boards.

Full journey: crawl → LLM analysis → skill gaps → mock interview

The whole loop in one terminal run, offline: 54 sample postings crawled and structured, resume×job skill gaps, and a mock interview with a feedback report. Replay it with python examples/full_journey_demo.py.

Try It in 2 Minutes (Demo Mode)

No API key? No problem. Demo mode runs the whole app offline:

pip install -e .
FINDJOBS_DEMO=1 python -m findjobs.api_server   # backend on :5000, seeds sample jobs on first run
cd FrontEnd && npm install && npm run dev   # frontend on :5173

With `FINDJOBS_DEMO=1`, the server fills an empty `jobs.db` from `data/sample_jobs.json` (54 hand-written postings from the companies the crawlers target) and routes every LLM call through `demo_llm.py`, a deterministic stub that answers from the prompt content and never touches the network, even if a key is configured. Up