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.
- 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.
The problem right now with something like this is you're trying to nail jello to a wall. People haven't figured out what an agent is yet, and trying to crystalize what people happen to be doing right now means in a few months, you're going to be obsolete.
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[ 3.2 ms ] story [ 25.8 ms ] threadI’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.