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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint=false. The description adds context by enumerating topics (population, income, education, employment, housing) and specifying that detail includes 'dimension levels and measures', plus its workflow role. It does not contradict annotations, and these additions go beyond the structured hints.

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?

Two compact sentences deliver the resource scope, the two usage modes, and the connection to the query tool. Information is front-loaded and every clause serves a purpose with no redundancy.

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 description is fully self-contained for a discovery/reference tool: it explains what it browses, how to list/filter, how to get details, and why one would use it (to plan a query). With 100% schema coverage Relation to sibling datausa.data.query is explicit. Given the output schema existsasi, absence of return-format details is not a gap.

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 100%, with each parameter (cube, limit, topic, search) already fully described in the schema, including default/max for limit and conditional behavior. The description references topic/keyword filtering but adds no new parameter-specific detail beyond the schema, so the baseline 3 applies.

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 explicitly states the verb 'Browse' (and later 'List' / 'fetch') applied to 'the 120+ data cubes (datasets) available on Data USA', immediately establishing the resource. It also distinguishes itself from the sibling datausa.data.query by stating its role is to 'plan a datausa.data.query call'.

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 gives explicit conditions: 'List cube names filterable by topic or keyword, or fetch full detail for one specific cube by name' and ties the tool's usage to planning a query. It also clarifies parameter behavior inline, e.g., 'Omit to list all available cubes instead' and 'Ignored when cube is set', leaving no ambiguity about when each mode applies.

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