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ArcadeData

ArcadeDB Multi-Model DBMS

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get_schema

Retrieve the complete database schema including vertex, edge, and document types with properties, indexes, and inheritance hierarchy for ArcadeDB Multi-Model DBMS.

Instructions

Get the full schema of a database including types (vertex, edge, document), their properties, indexes, and inheritance hierarchy.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
databaseYesThe name of the database

Implementation Reference

  • The 'getSchema' implementation in the python binding returns a Schema wrapper around the Java database's schema object.
    def schema(self):
        """
        Get the schema manipulation API for this database.
    
        The schema API provides type-safe access to schema operations:
        - Type management (document, vertex, edge types)
        - Property management (create, drop properties)
        - Index management (create, drop indexes)
    
        Returns:
            Schema instance for this database
    
        Example:
            >>> # Create a vertex type with properties
            >>> db.schema.create_vertex_type("User")
            >>> db.schema.create_property("User", "name", PropertyType.STRING)
            >>> db.schema.create_property("User", "age", PropertyType.INTEGER)
            >>>
            >>> # Create an index
            >>> db.schema.create_index("User", ["name"], unique=True)
            >>>
            >>> # Create edge type
            >>> db.schema.create_edge_type("Follows")
    
        Note:
            Schema changes are immediately persisted and visible to all
            database connections. Schema modifications should be done
            carefully in production environments.
        """
        self._check_not_closed()
        from .schema import Schema
    
        return Schema(self._java_db.getSchema(), self)
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes what is retrieved but lacks details on permissions required, rate limits, error conditions, or response format (e.g., JSON structure, size). For a read operation with no annotations, this leaves significant gaps in understanding how the tool behaves beyond its basic function.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose ('Get the full schema of a database') and elaborates with specific details (types, properties, etc.). There is no wasted text, and it is appropriately sized for the tool's complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (single parameter, read operation) and lack of annotations or output schema, the description is minimally adequate. It covers what the tool does but omits behavioral context and usage guidelines. Without an output schema, it should ideally explain return values, but it does not, leaving gaps in completeness for agent invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with the single parameter 'database' documented in the schema as 'The name of the database'. The description does not add meaning beyond this, such as format constraints or examples. With high schema coverage, the baseline score of 3 is appropriate, as the description does not compensate but also does not detract.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Get' and the resource 'full schema of a database', specifying what it retrieves: types (vertex, edge, document), properties, indexes, and inheritance hierarchy. It distinguishes from siblings like 'list_databases' (which lists names) or 'query' (which executes queries), making the purpose specific and well-differentiated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., needing an existing database), exclusions, or comparisons to siblings like 'get_server_settings' or 'server_status', leaving the agent to infer usage context without explicit direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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