Show HN: Kastor – Terraform-style specs for AI agents (github.com)

Kastor has emerged as a game-changer for the AI/ML community by introducing a new way to define AI agents through a Terraform-style specification. Unlike traditional, vendor-specific frameworks that often lead to fragmented and non-versioned agent definitions, Kastor offers a typed, declarative specification format (with .agent, .tool, and .prompt files in HCL) backed by a robust Go toolchain. This enables users to create and manage AI agents as long-lived resources on various platforms, incorporating features such as state management, drift detection, and a clear versioned source of truth. The significance of Kastor lies in its potential to unify and streamline the agent development process. By allowing users to generate runnable projects that are reproducible from their specifications, Kastor promises greater consistency and collaboration within AI development teams. With installation options that include Homebrew and a Go 1.26+ prerequisite, Kastor simplifies onboarding and usage. Additionally, the architecture supports complex scenarios, enabling agents to handle dependencies between various tools and ensuring that developers can easily manage the interactions between different components of their AI systems. This innovation positions Kastor as a pivotal tool in the evolution of AI agent frameworks, fostering enhanced productivity and collaboration in AI projects.