superset_dashboard_get_by_id

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool makes an API request to a specific endpoint and returns 'complete dashboard information including components and layout,' which provides useful context about what data to expect. However, it doesn't mention authentication requirements, error conditions, rate limits, or whether this is a read-only operation (though 'Get' implies it). The description adds some behavioral context but leaves significant gaps for a tool with zero annotation coverage.

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

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

The description is efficiently structured with a clear purpose statement first, followed by implementation details and parameter/return explanations. Every sentence adds value: the first states what it does, the second provides endpoint context, and the last two explain inputs and outputs. There's no redundant information or unnecessary elaboration, making it appropriately sized and front-loaded.

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

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) with no annotations and no output schema, the description provides a basic but incomplete picture. It covers the purpose, parameter meaning, and return format at a high level, but lacks details about authentication, error handling, or what specific fields the 'complete dashboard information' includes. For a tool with zero structured metadata, the description is adequate but has clear gaps that could hinder effective use.

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

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

The description adds meaningful context for the single parameter 'dashboard_id' by explaining it's 'ID of the dashboard to retrieve,' which clarifies its purpose beyond what the schema provides (which has 0% description coverage and only shows it's an integer). Since there's only one parameter and the description explains its role, this compensates well for the schema's lack of documentation. The description doesn't provide format details or constraints, but for a single parameter tool, this is sufficient.

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

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

The description clearly states the tool's purpose with a specific verb ('Get details') and resource ('for a specific dashboard'), making it immediately understandable. It distinguishes this tool from its sibling 'superset_dashboard_list' by focusing on retrieving a single dashboard rather than listing multiple. However, it doesn't explicitly differentiate from other 'get_by_id' tools like 'superset_chart_get_by_id' or 'superset_dataset_get_by_id' beyond the resource type.

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

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

The description implies usage context through the parameter explanation ('ID of the dashboard to retrieve'), suggesting this tool is for when you have a specific dashboard ID. However, it doesn't provide explicit guidance on when to use this versus alternatives like 'superset_dashboard_list' or what prerequisites might be needed (e.g., authentication). The context is clear but lacks explicit when/when-not statements or named alternatives.

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