Semantic Layer for Deterministic Domain State
Manifesto gives you one semantic model for deterministic domain state and tooling surfaces built from the same schema. Approval, history, and governance come later only when the project needs them.
npx @manifesto-ai/cli initThat opens the interactive init flow. Prefer pnpm or bun? Use pnpm dlx @manifesto-ai/cli init or bunx @manifesto-ai/cli init.
Prefer manual setup? Install @manifesto-ai/sdk for the app runtime. Install @manifesto-ai/compiler directly only when your project imports compiler entrypoints such as @manifesto-ai/compiler/vite.
domain Counter {
state { count: number = 0 }
action increment() {
onceIntent { patch count = add(count, 1) }
}
}
import { createManifesto } from "@manifesto-ai/sdk";
import CounterMel from "./counter.mel";
const app = createManifesto(CounterMel, {}).activate();
await app.dispatchAsync(
app.createIntent(app.MEL.actions.increment),
);
console.log(app.getSnapshot().data.count); // 1- Build the first app: Docs Home -> Guide Introduction -> Quick Start
- Set up CLI, editor, AI, or Studio workflows: Developer Tooling
- Add approval, review, or sealed history later: When You Need Approval or History
- Look up a package you already know: API Reference
- Go deeper into the model: Concepts, Architecture, Internals
Start with the base SDK runtime. Add compiler entrypoints, Lineage, Governance, or the surrounding DX packages only when the project actually needs them.
- Not a state management library
- Not an AI framework
- Not a database or ORM
- Not a workflow engine
Manifesto is a general-purpose declarative runtime. The underlying design philosophy and the initial empirical validation of its reflective protocol If you use this core framework in your research, please cite:
@misc{jung2026llmdoesselfrevisingagent,
title={How Much LLM Does a Self-Revising Agent Actually Need?},
author={Sungwoo Jung and Seonil Son},
year={2026},
eprint={2604.07236},
archivePrefix={arXiv},
primaryClass={cs.AI},
url={https://arxiv.org/abs/2604.07236},
}