evo.ninja
Health Warn
- License — License: MIT
- Description — Repository has a description
- Inactive repo — Last push was 620 days ago
- Community trust — 1079 GitHub stars
Code Pass
- Code scan — Scanned 12 files during light audit, no dangerous patterns found
Permissions Pass
- Permissions — No dangerous permissions requested
This tool is a versatile, generalist AI agent that adapts its behavior in real-time to accomplish user tasks. It cycles through different expert personas—such as a Researcher, Developer, or CSV Analyst—to autonomously execute steps until a goal is achieved.
Security Assessment
The automated code scan of 12 files found no dangerous patterns, hardcoded secrets, or requests for risky permissions, resulting in a preliminary Low risk rating. However, developers should be aware that its core architecture requires autonomy. By design, the agent dynamically evaluates tasks and executes functions, which inherently includes capabilities like internet research, reading local files, and running code (specifically noting Python expertise). Because the tool relies on an execution loop that acts on user prompts, you should rigorously sandbox its environment to prevent unintended file access or unwanted network requests during operation.
Quality Assessment
The project possesses a strong community footprint with over 1,000 GitHub stars and a clear MIT license, making it highly attractive for open-source collaboration. The main drawback is its maintenance status; the repository has been inactive for approximately 620 days. While the underlying code is stable enough to pass basic health checks, this prolonged dormancy means you will likely encounter outdated dependencies, unpatched vulnerabilities, and deprecated Node.js packages if you choose to build from source.
Verdict
Use with caution. The codebase itself appears safe and permissively licensed, but extreme inactivity and the inherent risks of autonomous task execution require you to implement strict local sandboxing and accept the burden of manually updating stale dependencies.
A versatile generalist agent.

Discord | :star: the repo !
Welcome!
To get started using evo.ninja simply head to our website, or to build and run from source follow these setup instructions.

Need Help?
Join our Discord community for support and discussions.
If you have questions or encounter issues, please don't hesitate to create a new issue to get support.
How it works
What makes evo.ninja special is that it adapts itself in real-time, based on the tasks at hand. Evo utilizes pre-defined agent personas that are tailored to specific domains of tasks. Each iteration of evo's execution loop it will select and adopt the persona that fits the task at hand best.
Agent Personas
| Agent | Expertise |
|---|---|
| 📝Synthesizer | "Reads text files, analyzing and gathering data and information from text files, generating summaries and reports, and analyzing text." |
| #️⃣ Csv Analyst | "Adept at reading CSV files, searching for data, extracting key data points, calculating amounts, and derive insights from CSV files." |
| 🌐 Researcher | "Searching the internet, comprehending details, and finding information." |
| 💻 Developer | "Architect and build complex software. specialized in python." |
Execution Loop

- Predict Next Step: For each iteration of the execution loop, Evo starts by making an informed prediction about what the best-next-step should be.
- Select Best Agent: Based on this prediction, Evo selects a best-fit agent persona.
- Contextualize Chat History: Based on the prediction from step 1, and the agent persona in step 2, the complete chat history is "contextualized" and only the most relevant messages are used for the final evaluation step.
- Evaluate and Execute: A final evaluation step is run to determine what agent function is executed to try and further achieve the user's goal.
These 4 steps run in a loop continuously until it is determined the user's goal has been achieved.
Setup
Pre-Requisites
Please install the following:
Installation
- Clone the repository
git clone https://github.com/agentcoinorg/evo.ninja - Copy the
.env.templatefile and rename it to.env.cp .env.template .env - Find the line that says OPENAI_API_KEY=, and add your unique OpenAI API Key
OPENAI_API_KEY=sk-... - Find the line that says SERP_API_KEY=, and add your unique SERP API Key.
SERP_API_KEY=b071...(see https://serpapi.com) - Use the correct version of Node.JS
nvm install && nvm use
Install Yarn if the node environment is newnpm install -g yarn - Install all dependencies & build project
yarn && yarn build
Now you're ready to go! You can run Evo through CLI or using the UI
CLI
Run evo in the terminal:
yarn start
Arguments:
[goal]- Goal to be achieved
Options:
-s, --session <name>- Name of the session within the./sessions/...directory.-t, --timeout <seconds>- Specify a timeout, used to terminate the process after a specified number of seconds.-d, --debug- Emit debug logs within the./sessions/${session}/.evo/...directory.
Session Workspace
Once the evo.ninja CLI is run, there will be a ./sessions directory created, with named sessions within it. This is the root directory for the agent, and only files within this directory will be read and written by the agent. There exists a .evo/ directory within each session workspace, where internal logs are kept, including a chat.md file that's provides a markdown version of the agent's output. Use --debug to get a raw debug log emitted here as well.
UI
The UI depends on Supabase Database. In order to run it locally you must have Docker Desktop installed and running.
- Make sure you've followed installation steps above
- Go to
cd apps/browser - Run
yarn db:start- This can take up to ~3 minutes, since it will download all the images needed by supabase - Update
.env.localwith the values shown in the output of step 2:NEXT_PUBLIC_SUPABASE_URLwill have the value ofAPI URLSUPABASE_SERVICE_ROLE_KEYwill have the value ofservice_role key
- Run the UI with
yarn dev
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