What does the agent.define skill actually do?

It validates agent.yaml configuration files for the Betty Framework and adds them to a central registry, ensuring they meet all structural and functional requirements.

Does this skill check if an agent's dependencies exist?

Yes, it specifically verifies that every skill listed in the 'skills_available' field is already registered in the system's skill registry.

What are the naming conventions for agents?

Agent names must be lowercase, start with a letter, and follow the . pattern, such as 'api.designer' or 'data.migrator'.

What is the difference between iterative and oneshot reasoning modes?

Iterative mode allows an agent to refine its output based on feedback and errors, while oneshot mode is for deterministic tasks that execute in a single pass.

What versioning system does agent.define use?

It enforces strict Semantic Versioning (SemVer), requiring a MAJOR.MINOR.PATCH format to ensure compatibility across the framework.

Agent Registry & Validation

Name: Agent Registry & Validation
Author: epieczko

byepieczko

Herramientas para Desarrolladores

Validates and registers agent manifests for the Betty Framework to ensure schema compliance and skill integration.

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The agent.define skill is a core utility for the Betty Framework designed to manage the lifecycle of AI agents. It acts as a gatekeeper for the Layer 2 Reasoning Layer by validating agent.yaml manifests against strict schema requirements, including semantic versioning, naming conventions, and reasoning modes. By verifying that all referenced skills exist in the registry and automatically updating the central agent directory, it ensures that your AI ecosystem remains stable, well-documented, and ready for orchestration.

Características Principales

Cross-reference verification with the existing skill registry
Validation of reasoning modes (iterative vs. oneshot)
0 GitHub stars
Enforcement of semantic versioning and domain-based naming
Automated manifest schema validation for agent.yaml files
Dynamic registration and updates to the central agents.json registry

Casos de Uso

Standardizing AI agent definitions within a multi-agent architecture
Ensuring newly developed agents have all required dependencies registered
Maintaining a centralized and versioned directory of available AI capabilities

Acerca de

Características Principales

Cross-reference verification with the existing skill registry
Validation of reasoning modes (iterative vs. oneshot)
0 GitHub stars
Enforcement of semantic versioning and domain-based naming
Automated manifest schema validation for agent.yaml files
Dynamic registration and updates to the central agents.json registry

Casos de Uso

Standardizing AI agent definitions within a multi-agent architecture
Ensuring newly developed agents have all required dependencies registered
Maintaining a centralized and versioned directory of available AI capabilities