superset_dataset_related_objects

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

No annotations are provided, so the description must carry the behavioral disclosure burden. It clearly states that 'Get' is a read operation and describes the return type as a 'JSON string with related charts and dashboards.' However, it does not discuss potential errors, permissions, or any side effects, leaving some gaps in transparency.

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 concise and well-structured with separate sections for purpose, usage, args, and returns. Every sentence adds useful information without padding.

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?

For a simple one-parameter lookup tool, the description covers the essential aspects: purpose, when to use, the input parameter, and the return type. An output schema is noted, so detailed return structure is not required. It is missing some edge-case behavior (e.g., empty results) but is reasonably complete given the tool's simplicity.

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 schema has one required parameter, dataset_id, with no descriptions. The description adds a 'Dataset ID' label for the argument, which slightly clarifies the parameter but does not go beyond what the parameter name already implies. Since schema coverage is 0%, the description partially compensates but not richly.

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 specific action ('Get objects related to a dataset') and explicitly narrows the scope to 'charts and dashboards'. This distinguishes it from sibling tools like superset_database_related_objects and superset_dashboard_datasets.

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?

It provides an explicit use case: 'Useful before deleting a dataset to understand the impact.' This is clear context for when to use the tool, though it does not mention alternatives or when not to use it.

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