useless-agent

Vote for the useless-agent cloud! https://useless-agent.xyz

What can this agent do? Basically nothing, that’s why it is the useless-agent.

Why is it interesting?

• Uses text-only LLMs.
• Cheap: I spent about $4.57 playing with it for about 7 evenings.
• Single binary. (almost, see todo list)
• Easy to use: run the binary and copy the IP address.
• No telemetry, no bullshit.
• IPv4 & IPv6(*should work, not tested yet)

⭐ Would you like me to work more on this project? Please consider giving this repository a star!

Caution

• Only use this on a disposable virtual machine.
• It can, and most likely will, destroy your system.
• The LLM API provider has a realistic ability to inject malicious commands/actions/data into the ingested API responses.
• The video is not compressed. If you are connected to a virtual machine in the cloud, be aware of high internet traffic.
• The video stream and everything else, except the API queries, are not encrypted. If connecting to a remote machine, use an SSH tunnel with port forwarding.

Note

It is super slow. Right now, speed is not a priority. If your only problem is speed, you have already won the agents game.

Currently supported llm providers:

• DeepSeek
• Z.AI

Currently supported models:

• deepseek-chat
• deepseek-reasoner
• glm-4.6
• glm-4.5
• glm-4.5-air
• glm-4.5-flash

Environment: Only works on - Linux + xfce + X11.

Changelog

v0.0.3

• User-assist feature works.
• Faster task cancellation.
• Extract css and js from the html file.
• Fixed routing of the line which connects chat and session window.
• Fixed media buttons overlay resizing.
• Tasks destined to the same session now queued.
• Use more API of the environment where it's possible.
• Break main.go into separate packages.
• Other small fixes.

v0.0.2

• Manage multiple sessions at once.
• Fullscreen & maximize control elements for the video stream. Hotkeys F and M.
• Added a button to the task card to reopen a session window.
• MVP of the user-assist feature, only UI for now.
• Smart scrolling for the tasks section.
• Many small UI bugfixes and improvements.

Multi-session

User-assist

v0.0.1

• Added basic tasks management and status indication.
• Hotkeys support.
• UI update.
• Video stream FPS selector.

Q&A

• Can I put something like http://127.0.0.1:11434/v1 into API_BASE_URL='' and use a model that I run locally? - Yes.

Demos

Prompt: Open a web browser and go to deepseek.com

demo-1-compressed-2.mp4

Prompt: Very detailed prompt to create a ping pong tcp client and server(neovim)

demo-2.mp4

How to build:

The easiest way:

docker compose up --build

For more information, see DOCKER_README.md.

Warning

Docker is not a sufficient level of isolation and it is risky.

or manually:

• git clone
• cd useless-agent
• go build

How to prepare headless vm:

Scripts - "assets/scripts"

sudo apt update && sudo add-apt-repository ppa:alex-p/tesseract-ocr5 && sudo apt install -y \
  xfce4 xvfb tesseract-ocr-eng tesseract-ocr libtesseract5 libleptonica-dev libtesseract-dev
sudo apt remove -y xfce4-screensaver
sudo systemctl enable --now xvfb.service xfce4.service

How to establish a secure tunnel between client and remote server:

ssh -p 22 -fN -o IPQoS=ef USERNAME@REMOTE-HOST-PUBLIC-IP -L 127.0.0.1:8080:127.0.0.1:8080

How to use:

copy executable to the target machine

start executable:

./useless-agent --provider=deepseek --base-url="https://api.deepseek.com/v1" --key=YOUR-API-KEY --model='deepseek-chat' --display=:1 --ip=127.0.0.1 --port=8080
./useless-agent --provider=zai --base-url="https://api.z.ai/api/paas/v4" --key="YOUR-API-KEY" --model='glm-4.5-air' --display=:1 --ip=127.0.0.1 --port=8080

On client machine open main.html in the browser.

Put target machine IP into the field "IP Address".

Click "Connect".

Give it some task, for example "Open web browser", put that prompt into the LLM Chat and press "Send".

Tip

Like to burn money? Try more capable LLMs; using DeepSeek R1 instead of v3 would probably make the program more capable of doing nothing.

Todo list:

• Build a single fully static binary.
• Add stats about burned tokens.
• Allow LLM to spawn local 'thoughts', which would do/monitor something and then allow them to interrupt the main LOOP and to inject its results into the thinking loop.
• Build a unified concept space for models that are capable of ingesting more data.
• Pause task execution.
• Allow intervention in the execution process and provide guidance/additional instructions.

Problems & Ideas:

• LLMs' context window/input size is so limiting; I want to shuffle in 100M million tokens at each iteration.
• How to do reliable OCR? Don’t do it at all. The idea was to find a single point where Linux renders fonts for the whole system and intercept it, to set something like an eBPF hook and get all text for free. Turns out there is no single point of font rendering in Linux! Each X11 client app is allowed to render fonts itself. Nice.
• How hard could it be to write a single function to recognize windows? They have unified patterns, right? Wrong. Each window is allowed to draw its own header however they like. I’m looking at you, Firefox. Nice.