Recruitment Recommendation Agent

Visit Tool

Recruitment Recommendation Agent is an AI agent that autonomously applies to relevant jobs online. It controls your browser to search and apply for jobs based on your resume and preferences.

Claim this tool

1View

At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is Recruitment Recommendation Agent?

Jobber is an AI agent designed to automate the job application process by controlling your web browser. Users provide their resume and job preferences, and the agent autonomously searches for and applies to relevant jobs online. The tool offers two implementations: a simpler multi-agent conversation approach and a more scalable finite state machine (FSM) approach. While the FSM version offers better scalability, it relies on structured output from OpenAI, making it less compatible with cheaper or open-source models. Jobber is built on the open-source framework 'sentient,' which aims to help developers build fast and reliable AI agents for browser control with minimal code.

Best used for

Ideal for job seekers who need to automate the tedious process of applying for jobs, manage their application preferences, and efficiently search for relevant roles. Especially valuable for developers interested in building and experimenting with browser-controlling AI agents.

Common actions

automate job applications

control browser autonomously

manage job search

build AI agents

"AI Agents"github copilotautomated workflowopen-sourcecollaborationface swappingdeepfakelow-code/no-codeworkflows

Capabilities

Key features

Autonomous job application
Browser control
Resume upload
Preference-based job search
Multi-agent conversation
Finite state machine

Target Audience

job seekerdeveloper

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What is the difference between the 'jobber' and 'jobber_fsm' implementations?

The 'jobber' folder contains a simpler multi-agent conversation approach, while 'jobber_fsm' uses a finite state machine for better scalability. The FSM approach requires structured output from OpenAI, making it less suitable for cheaper or open-source models compared to the 'jobber' setup.

What are the prerequisites for running Jobber?

To run Jobber, you need to install Poetry, start Chrome in dev mode with remote debugging enabled, set up your OpenAI and Langsmith keys in a .env file, and update your job preferences and resume path in the user_preferences.txt file.

Can I use Jobber with open-source LLMs?

The 'jobber' implementation is more flexible and can potentially work with cheaper or open-source models. However, the 'jobber_fsm' approach is dependent on structured output from OpenAI, making it less reliable with models like gpt4o-mini or other open-source alternatives.

Trending

Subcategories trending in AI Agents & Automation

AI Frameworks & Infra Chatbots & Conversational AI Workflow Agents Personal Assistants RAG & Document AI Voice Agents

Trending

Explore

Browse AI tools by category

Content & Design Productivity & Business Coding & Development AI Agents & Automation Research & Education Wellness & Lifestyle Career Development Marketing & Growth Data & Analytics Customer Support & CX Finance E-commerce