*This is a submission for the [Hermes Agent Challenge]
What I Built
Hermes Commander is my first AI agent project built using Hermes Agent.
The goal of this project was to explore how an AI agent can go beyond simple question-answering and perform structured tasks using tools. Hermes Commander acts as an autonomous research assistant that can understand requests, create research plans, access available tools, and organize workflows.
As someone interested in AI, prompt engineering, and research, I wanted to build an agent that could help investigate technical topics in a more structured and agentic way.
Current capabilities include:
Agent identity and interaction
Agentic task planning
Tool discovery and management
Research workflow generation
Browser-assisted information gathering
Structured task execution
This project represents my first step into building autonomous AI systems and serves as the foundation for future research-focused agents
Demo
https://www.youtube.com/watch?v=YatyrfyPq_U
Screenshots
Agent Introduction
Shows Hermes Commander identifying itself as an AI agent.
Agentic Capabilities
Demonstrates how the agent understands and explains its autonomous workflow.
Tool Access
Displays the tools available to the agent for planning and task execution.
Research Planning
Shows the agent creating a structured research plan for investigating AI agent frameworks.
Browser Navigation
Demonstrates browser-assisted navigation and information analysis.
Code
GitHub Repository:
https://github.com/AI-Explorer786/Hermes-Commander
My Tech Stack
Hermes Agent
Google Gemini
Ubuntu (WSL)
Browser Automation Tools
GitHub
Markdown Documentation
How I Used Hermes Agent
Hermes Agent serves as the core engine behind Hermes Commander.
I used Hermes Agent to:
Create structured research plans
Manage task workflows
Access and utilize available tools
Interact with browser capabilities
Execute agent-driven reasoning processes
One of the most interesting aspects of Hermes Agent is its ability to act as more than a chatbot. Instead of only generating responses, it can plan actions, select tools, and perform multi-step workflows.
For this project, I focused on agentic capabilities such as:
Autonomous planning
Tool awareness
Workflow generation
Browser-assisted exploration
Research task organization
This allowed me to transform a standard AI interaction into a more agent-oriented experience where the system can reason about tasks and determine how to approach them.
Future Improvements
Future versions of Hermes Commander will include:
Local model support through Ollama
Advanced autonomous research workflows
Multi-step web research and summarization
Report generation
Knowledge memory and retrieval
Enhanced research automation
Building Hermes Commander was an exciting learning experience and my first practical step toward creating more capable AI research agents.