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GitHub · interviewstreet/hiring-agent↑ +203 today

Resume evaluation with artificial intelligence

Hiring-agent is an artificial intelligence agent (AI agent) designed to evaluate and score resumes. This tool, developed with Python language, aims to automate candidate screening processes in recruitment processes.

Updates

  • August 2, 2026: Stars 2,482 → 6,694.

What you get

  • It automatically parses resumes in PDF format.
  • It enriches candidates with GitHub data.
  • Provides a fair and explainable scoring report.

Installation

Downloading and installing the necessary files
git clone https://github.com/interviewstreet/hiring-agent
cd hiring-agent

python -m venv .venv
# Linux or macOS
source .venv/bin/activate
# Windows
# .venv\Scripts\activate

pip install -r requirements.txt

Running it

Start resume review
python score.py /path/to/resume.pdf

If you don't write code

Paste this into your AI agent (Claude Code · Codex · Antigravity)

Act as a recruiter and analyze provided resume data and technical contributions on GitHub. Score the candidate's projects, technical skills and work experience according to objective criteria. When scoring, consider the candidate's code quality on GitHub, frequency of contributions, and relevance of their projects to real-world applications. Ultimately, create a transparent and fair evaluation report that highlights the candidate's strengths and weaknesses.

Repository: https://github.com/interviewstreet/hiring-agent. Follow the official instructions in the README of this repository for setup and execution.

Before starting, check which OS we are on and if the necessary tools (e.g., Python, Node.js, Git, Docker) are installed. Install any missing ones step-by-step according to this system.

Create a new, empty folder to work in. Do not touch any files outside this folder and do not delete anything. Tell me what you are going to do in one sentence before running each command.

Tell me what I should see on the screen at the end of each step. If an error occurs, I will paste the error message to you exactly as it is, and we will fix it together.

Related dictionary terms

Who it is forIt is for technical managers and HR professionals who want to speed up their recruitment processes and evaluate candidates with data-driven methods.
LicenseMIT

Links

TreScout did not build this tool · we found it in GitHub trends and wrote it up. This page describes the repository as of 2026-06-25: The star count and our text belong to that day, the repository may have changed since. Check the repository link for the current state. The introductory text was prepared with AI from the repository's own documentation, and this page was machine-translated from the Turkish original · the Turkish version prevails.