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World of Software > News > Next Moca Releases Agent Definition Language as an Open Source Specification
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Next Moca Releases Agent Definition Language as an Open Source Specification

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Last updated: 2026/02/09 at 2:07 AM
News Room Published 9 February 2026
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Next Moca Releases Agent Definition Language as an Open Source Specification
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Moca has open-sourced Agent Definition Language (ADL), a vendor-neutral specification intended to standardize how AI agents are defined, reviewed, and governed across frameworks and platforms. The project is released under the Apache 2.0 license and is positioned as a missing “definition layer” for AI agents, comparable to the role OpenAPI plays for APIs.

ADL provides a declarative format for defining AI agents, including their identity, role, language model setup, tools, permissions, RAG data access, dependencies, and governance metadata like ownership and version history. The aim is to enhance the portability, auditability, and interoperability of agents across various platforms and vendors.

The release addresses a growing fragmentation problem in agent development. Today, agent behavior is often spread across prompts, code, framework-specific configuration files, and undocumented assumptions. This makes it difficult for teams to answer basic questions about an agent’s capabilities, boundaries, and approval status, and complicates security reviews, compliance, and reuse.

ADL consolidates agent definitions into a structured, machine-readable format to enhance inspectability and governance. It is framework-agnostic and focuses on definitions rather than execution, without addressing agent communication, runtime tool invocation, or message transport. ADL is intended to complement existing technologies like A2A, MCP, OpenAPI, and workflow engines.

Announcing the open-source release, Next Moca founder Kiran Kashalkar described ADL as “Think OpenAPI (Swagger) for agents,” adding that it provides “a single, declarative spec that says what an agent is, what tools it can call, what data it can touch, and how it is configured.” Kashalkar emphasized portability, auditability, and vendor neutrality as core design goals.

According to Next Moca, ADL is aimed at teams building production AI systems, where agents increasingly operate as autonomous components with access to tools, data, and external systems. The company argues that a standardized definition layer enables clearer planning, consistent validation in CI pipelines, explicit comparison of agent capabilities, and software-style lifecycle management through versioning and rollback.

The project includes a published JSON Schema, example agent definitions, validation tools, and documentation covering governance and contribution processes. Developers can define an agent once and validate it locally, then share the same definition across security, platform, and compliance teams.

Next Moca describes ADL as an early-stage standard and is inviting community feedback and contributions to shape its evolution. The company states that open-sourcing the specification is intended to encourage broad adoption, neutral governance, and the development of an ecosystem of editors, validators, registries, and testing tools around a shared format.

The ADL repository and documentation are available on GitHub, with contribution guidelines and a public roadmap outlining planned next steps.

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