get_cube_structure

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

Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds valuable behavioral context beyond those hints: it returns a licence that is often a Fedlex URI, and it discloses the semantic structure of the response (KeyDimension, MeasureDimension). There is no contradiction with the annotations.

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 front-loaded with a concise purpose statement followed by a compact explanation of what the tool tells the agent. The Args section is clearly separated and each sentence delivers useful information without filler. It is appropriately sized for the tool's complexity.

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 presence of an output schema, the description does not need to detail return structure. It covers the tool's role in the workflow, parameter semantics, the licensing edge case, and its relationship to sibling tools, making it complete for a read-only structure-resolution tool.

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 no descriptions for cube_uri or language (0% schema description coverage), so the description carries the full burden. The Args section explains that cube_uri comes from search_cubes and that language controls dimension names and descriptions, fully compensating for the schema's lack of semantic detail.

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 opens with a specific verb+resource ('Read a cube's dimensions and measures') and immediately differentiates from siblings by labeling it 'phase 1' of the two-phase access pattern. It also clarifies what kind of data is returned (dimensions, measures, code lists), distinguishing it from query_cube_observations.

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 explicitly states 'always call this before data' and frames the tool as 'phase 1', telling the agent exactly when to invoke it. It also describes what information the tool reveals (filterable dimensions, measured values, code lists) and how to handle the licence (Fedlex URI resolution), providing clear decision guidance.

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