Better Agents is a CLI tool and a set of standards for agent building.
It supercharges your coding assistant (Claude Code, Cursor, Kilo Code, etc), making it an expert in any agent framework you choose (Agno, Mastra, etc) and all their best practices and agent building best practices we collected over this past two years.
Better Agents brings an opinionated folder structure to your agent application:
my-agent-project/
├── app/ (or src/) # The actual agent code, according to the chosen framework
├── tests/
│ ├── evaluations/ # Jupyter notebooks for evaluations
│ │ └── example_eval.ipynb
│ └── scenarios/ # End-to-end scenario tests
│ └── example_scenario.test.{py,ts}
├── prompts/ # Versioned prompt files for team collaboration
│ └── sample_prompt.yaml
├── prompts.json # Prompt registry
├── .mcp.json # MCP server configuration
├── AGENTS.md # Development guidelines
├── .env # Environment variables
└── .gitignore
The structure and guidelines on AGENTS.md ensure every new feature required for the coding assistant is properly tested, evaluated, and that the prompts are versioned.
The `.mcp.json` comes with all the right MCPs set up so you coding assistant becomes an expert in your framework of choice and know where to find new tools.
`scenarios/` tests guarantee the agent behaves as expected, which simulates a conversation with the agent making sure it does what expected.
`evaluations/` notebooks holds dataset and notebooks for evaluating pieces of your agent pipeline such as a RAG or classification tasks it must do
Finally, `prompts/` hold all your versioned prompts in yaml format, synced and controlled by prompts.json, to allow for playground and team collaboration.
We defined it and built the CLI after seeing many of our customers having to adapt their codebases and ways of working to add scenario tests and more structure to their agent apps. We are hoping to shift-left the industry and already start new agent projects the right way.
Better Agents is a CLI tool and a set of standards for agent building.
It supercharges your coding assistant (Claude Code, Cursor, Kilo Code, etc), making it an expert in any agent framework you choose (Agno, Mastra, etc) and all their best practices and agent building best practices we collected over this past two years.
Better Agents brings an opinionated folder structure to your agent application:
my-agent-project/
├── app/ (or src/) # The actual agent code, according to the chosen framework
├── tests/
│ ├── evaluations/ # Jupyter notebooks for evaluations
│ │ └── example_eval.ipynb
│ └── scenarios/ # End-to-end scenario tests
│ └── example_scenario.test.{py,ts}
├── prompts/ # Versioned prompt files for team collaboration
│ └── sample_prompt.yaml
├── prompts.json # Prompt registry
├── .mcp.json # MCP server configuration
├── AGENTS.md # Development guidelines
├── .env # Environment variables
└── .gitignore
The structure and guidelines on AGENTS.md ensure every new feature required for the coding assistant is properly tested, evaluated, and that the prompts are versioned.
The `.mcp.json` comes with all the right MCPs set up so you coding assistant becomes an expert in your framework of choice and know where to find new tools.
`scenarios/` tests guarantee the agent behaves as expected, which simulates a conversation with the agent making sure it does what expected.
`evaluations/` notebooks holds dataset and notebooks for evaluating pieces of your agent pipeline such as a RAG or classification tasks it must do
Finally, `prompts/` hold all your versioned prompts in yaml format, synced and controlled by prompts.json, to allow for playground and team collaboration.
We defined it and built the CLI after seeing many of our customers having to adapt their codebases and ways of working to add scenario tests and more structure to their agent apps. We are hoping to shift-left the industry and already start new agent projects the right way.