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Aontu is a JSON-superset language for defining system models. It treats model documents as constraints: combining them through unification produces the most specific value that satisfies both, or an error if they conflict. That idea links its schema checks, output generation, error reports, JSON Schema export, and schema-evolution commands—but those operations do different jobs.
What is Aontu?
Aontu is an open-source language for describing entities, their fields and types, and relations between them. Because it is a superset of JSON, ordinary JSON documents are valid Aontu input; additional constraints can describe which values a model admits. The project says its unification approach is inspired by CUE. Aontu’s project overview summarizes the central rule: “Two documents unify into the most specific value that satisfies both, and where they cannot, the result is an error that names the contradiction and where it is.”
The project overview also lists command-line and MCP-server operations for checking, querying, explaining, setting, and comparing definitions. These are document-oriented operations, not interchangeable names for a single validation step.
What does inference mean in Aontu?
“Inference” can suggest that a system automatically fills in every unknown. The documented Go API makes a more precise distinction: parsing, unification, checking, and generation are separate stages.
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- Parsing produces an abstract syntax tree (AST) from the source.
- Unification combines constraints and can fail when they conflict.
- Check reports issues without rejecting a schema merely because it is not concrete. The Go API documentation gives
a:stringas an example of a schema that is valid forCheck. - Generation produces native values and requires the result to be fully concrete. A schema that still leaves values unspecified may therefore pass a check but not be generatable yet.
In the Go API, documented generated values include maps, lists, strings, integers, floats, big integers or decimals, booleans, and null. The reference specifically calls out exact numeric leaves for explicit 0d values. Those are Go API details; they should not be assumed to describe every implementation identically. See the Go package reference.
Can Aontu export a schema to JSON Schema?
Yes. The Go API provides JSONSchema(src, at); the at argument selects a subtree to export. The returned SchemaReport includes the schema and a Lossy list. Each loss item identifies an Aontu construct and path, explains why JSON Schema could not express it, and records what was emitted instead.
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Inspect Lossy when relying on an export: the conversion does not necessarily preserve every Aontu construct. The API reference documents this behavior at pkg.go.dev.
How should you read an Aontu error?
Start with the reported contradiction or issue and its location. The project describes unification conflicts as errors that identify both what is inconsistent and where it occurs. In the Go API, error information has machine-readable and human-readable parts:
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AontuErrorincludes a message and error code, and provides row and column information for parse failures.Problemincludes a reason code, a registered class, and a readable message. Documented classes include conflict, incomplete, reference, parse, budget, and internal.- The API describes a location-aware full message that can include an
[aontu/<code>]marker, an attempt or path headline, hints, and source frames.
Use codes for programmatic handling rather than matching message text: the API says codes are intended to have cross-implementation parity and are registered in a shared error-code registry. Exact wording and formatting should not be treated as identical for every error or implementation. The reference does not enumerate the complete registry. The Go API documentation describes these error surfaces.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How can you check schema evolution?
The project overview lists breaking as a schema-evolution command. A related use-case reference demonstrates aontu subsume reporting.aontu domain.aontu. In that example, “subsumes” means every document admitted by the domain schema is also admitted by the reporting view. This makes subsumption useful for comparing the sets of inputs two schemas accept.
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For a change review, the documented tools suggest several distinct questions:
- Does one schema subsume the other, based on the documents each admits?
- Does the project’s
breakingcheck report the change as breaking? - If you need JSON Schema, does export report constructs that could not be represented?
The available references establish these as useful comparison axes, not a complete migration decision table. They do not specify every breaking-change rule, a rollout sequence, or a universal migration policy. Treat the commands as compatibility checks, not as a full migration recipe, and consult the documentation for the version you use before making release-specific decisions. See the project overview, use-case reference, and Go API reference.
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Which Aontu implementation should you use?
The official project page describes TypeScript and Go implementations held to a shared test suite, and the Go package reference provides a native Go API. Choose the implementation that fits your project language and integration needs. The cited references do not establish a comparative performance benchmark or an exhaustive feature matrix, so they do not support a claim that one implementation is faster or more capable.
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