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get_dashboard_types

Retrieve available chart types for creating dashboards in the Devici security platform to visualize threat models and security data.

Instructions

Get available dashboard chart types

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • MCP tool handler for 'get_dashboard_types'. Decorated with @mcp.tool(), it creates an API client and calls its get_dashboard_types method, returning the result as string.
    @mcp.tool()
    async def get_dashboard_types() -> str:
        """Get available dashboard chart types"""
        async with create_client_from_env() as client:
            result = await client.get_dashboard_types()
            return str(result)
  • Helper method in the API client that makes a GET request to '/dashboard/types' to retrieve available dashboard types.
    async def get_dashboard_types(self) -> List[str]:
        """Get dashboard chart types."""
        return await self._make_request("GET", "/dashboard/types")
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. The description only states what the tool does ('Get available dashboard chart types') without revealing whether this is a read-only operation, what authentication is required, whether results are cached, or what format the output takes. For a tool with zero annotation coverage, this is insufficient.

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 states exactly what the tool does with zero wasted words. It's appropriately sized for a simple lookup tool and is front-loaded with the core functionality.

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 that the tool has zero parameters, 100% schema coverage, and an output schema exists, the description doesn't need to explain parameters or return values. However, as a metadata discovery tool with no annotations, it should ideally provide more context about when and why to use it, especially with similar-sounding sibling tools. The description is minimally adequate but lacks helpful contextual guidance.

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

Parameters4/5

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

The tool has zero parameters, and schema description coverage is 100% (though there are no parameters to describe). The description doesn't need to compensate for missing parameter documentation since there are none. A baseline of 4 is appropriate for a parameterless tool where the schema fully covers the non-existent parameters.

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

Purpose4/5

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

The description 'Get available dashboard chart types' clearly states the verb ('Get') and resource ('dashboard chart types'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_dashboard_data' which might retrieve actual dashboard data rather than chart type metadata.

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. With sibling tools like 'get_dashboard_data' that might retrieve actual dashboard content, there's no indication whether this tool should be used for metadata discovery before creating dashboards or in what context it's appropriate.

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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