Reading
tool_schema_generator frees Dart developers from the tedious task of manually writing JSON Schemas, allowing automatic generation of LLM tool definitions compatible with OpenAI, Anthropic, and Gemini via annotations.
Section 01
tool_schema_generator frees Dart developers from the tedious task of manually writing JSON Schemas, allowing automatic generation of LLM tool definitions compatible with OpenAI, Anthropic, and Gemini via annotations.
Section 02
Section 03
When building AI Agents, developers often need to provide callable tool (function) definitions for large language models (LLMs). These definitions are usually presented in JSON Schema format, describing the tool's parameters, types, and purposes. However, manually writing and maintaining these Schemas is both tedious and error-prone, especially when the number of tools increases or parameters change.
For Dart developers, this problem is particularly prominent. As a strongly typed language, Dart's type system should naturally provide advantages for Schema generation, but in the past, there was a lack of an automated tool that could fully leverage this advantage. tool_schema_generator was born precisely to address this pain point.
Section 04
tool_schema_generator is a Dart code generator that can automatically generate tool definitions conforming to the JSON Schema Draft 2020-12 standard from annotated Dart functions. The main features of this project include:
Section 05
This tool can directly infer types, names, and nullability from Dart syntax, without requiring developers to write additional mapping code. This means you can focus on writing business logic while letting the generator handle the tedious Schema conversion work.
Section 06
Supports String, int, double, bool, List, Map, enum types, and custom nested classes. This comprehensive type coverage ensures that complex Dart data structures can be accurately converted to JSON Schema.
Section 07
This is one of the tool's most notable features. It can generate tool Schema formats required by three mainstream LLM platforms—OpenAI, Anthropic, and Gemini—from the same Dart function. Developers do not need to maintain multiple sets of Schema definitions for different platforms.
Section 08
Uses the standard source_gen builder, outputs to .g.dart files, and can collaborate perfectly with other code generators like json_serializable. This design choice allows it to integrate into existing Dart project workflows.
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