I’m building Kastor: Go CLI/declarative language/config for AI agents.
the motivation: agent definitions often end up spread across framework code, prompt files, tool files/mcps, platform UI settings, and env vars. that makes them hard to review, diff, reproduce or move.
Kastor is an attempt to put a source-of-truth layer above that.
right now the working proof of concept is narrow:
- .agent / .tool / .prompt files - HCL parser + validation - dependency/reference checks - LangGraph codegen - runnable weather example - runnable content scheduler example
the long-term direction is Terraform-ish:
- build: compile to framework code - plan/apply: reconcile hosted platform agents - state: track remote resources and detect drift
I’m deliberately not trying to build another agent runtime. the thing I’m trying to validate is whether agents need something closer to IaC: versionable, reviewable, declarative source of truth.
would appreciate any kind of feedback, especially on the language/design.
don't think the "agent" abstraction is stable enough to standardize the behavior/runtime layer yet.
thing I'm trying to test is smaller: is that possible to standardize the outer contract around agents?
what inputs does it accept? what outputs does it promise? what model does it use? what prompt/template does it depend on? what tools can it call? what target should it be built or applied to?
so here it is intentionally not trying to describe the full control loop or become a runtime. it's more like a source-of-truth layer for the parts that are already showing up everywhere, even if the runtime patterns keep changing underneath.
I might be wrong, but my bet is that the runtime layer will keep changing, while the need for reviewable/diffable agent contracts will not.