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Manage AI agent environments and configs declaratively with a Rust-based tool.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "kasetto" yet — see the docs or source repo.
Generate a declarative configuration for a local AI agent environment, including model provider, API key variables, log level, and working directory, with field explanations.
A clear sample agent environment configuration with explanations of each field.
Design a declarative setup for switching between development, testing, and production AI agent environments, and list recommended config structure and naming conventions.
A multi-environment configuration strategy plus best practices for switching and maintenance.
My AI agent environment fails to start. Give me a troubleshooting checklist focused on declarative config issues like dependencies, variable injection, permissions, and path settings.
An actionable troubleshooting checklist to identify and fix environment configuration problems.
Use cloud-native AI agents to handle development, DevOps, and automation tasks.
Manage terminal sessions for multiple AI coding agents in one unified interface.
Lets AI agents design hardware in C-like HDL and verify Verilog output.
Build AI agents quickly with a model-driven approach and minimal code.
Scaffold, compose, and upgrade modern multi-language projects for AI agents.
Provide AI agents a local sandbox to run code and tasks safely.