superset_dashboard_datasets

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

No annotations are present, so the description carries the full burden. It conveys a read-only operation ('Get') but does not disclose additional behaviors such as error conditions, permission requirements, or response size. The return format is presumably covered by the output schema, but the description itself provides minimal context beyond the 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.

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

The description is exceptionally concise: two sentences for purpose/usage and a minimal Args block. It front-loads the core function, avoids redundancy, and every sentence contributes value. Well-structured for quick agent scanning.

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?

The tool is simple with a single required parameter and an output schema exists, which reduces the burden on the description. Purpose, use case, and parameter are all covered succinctly. However, it could benefit from a brief mention of the output structure or typical use cases relative to dashboard-related siblings, but overall it is complete enough for this level of complexity.

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?

Schema description coverage is 0%, so the description must compensate. The Args section only restates the parameter name ('dashboard_id: Dashboard ID') without adding meaningful guidance on source, format, or usage. This is not enough to compensate for the missing schema description.

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 uses a specific verb+resource pattern ('Get the list of all datasets used by a dashboard's charts'), making the tool's purpose unambiguous. It clearly distinguishes itself from broader tools like superset_dashboard_get or superset_dataset_list, though it does not explicitly reference sibling tool names.

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 a clear use case ('Useful for understanding the dashboard's dependencies on data sources'), which implies when to use the tool. However, it lacks explicit exclusions or mentions of alternative tools like superset_dashboard_charts, so the guidance is somewhat implicit rather than fully articulated.

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