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Comprehensive JSON схема Tools for Every Need

Get access to JSON схема solutions that address multiple requirements. One-stop resources for streamlined workflows.

JSON схема

  • OpenAgentSpec

    An open specification defining standardized interfaces and protocols for AI agents to ensure interoperability across platforms.
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    What is OpenAgentSpec?
    OpenAgentSpec defines a comprehensive set of JSON schemas, API interfaces, and protocol guidelines for AI agents. It covers agent registration, capability declaration, messaging formats, event handling, memory management, and extension mechanisms. By following the spec, organizations can create agents that communicate reliably with each other and with host environments, reducing integration effort and fostering a reusable ecosystem of interoperable AI components.
    OpenAgentSpec Core Features
    • Standardized JSON schemas for agent capabilities
    • Protocol definitions for messaging and events
    • Agent registration and discovery interfaces
    • Extension mechanisms for custom agent behaviors
    • Conformance test suite and validators
    OpenAgentSpec Pro & Cons

    The Cons

    Limited public information on open source availability.
    No direct consumer-facing product details provided.

    The Pros

    Focuses on AI agent standards and interoperability.
    Supports development of structured specifications for AI agents.
    Aims to facilitate communication and collaboration between AI agents.
    OpenAgentSpec Pricing
    Has free planNo
    Free trial details
    Pricing model
    Is credit card requiredNo
    Has lifetime planNo
    Billing frequency
    For the latest prices, please visit: https://openagentspec.org

  • Xemantic AI Tool Schema

    A TypeScript and JSON Schema library enabling developers to define and validate AI agent tool interfaces type-safely
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    What is Xemantic AI Tool Schema?
    Xemantic AI Tool Schema is a set of JSON Schema and TypeScript type definitions designed to standardize the way AI agent tools are described, validated, and invoked. Developers can define tool metadata such as name, description, and parameters, then validate instances against the schema or use generated TypeScript interfaces during development. The schema supports parameter types, nested structures, default values, and version control, ensuring robust validation and compatibility. By following a consistent schema, AI Agents can discover and call tools reliably at runtime, improving maintainability and reducing integration errors. The package integrates seamlessly with Xemantic AI Agents and can be extended for custom use cases.
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