get_options

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

No annotations provided, so description bears full burden. Discloses that dimensions can be large and suggests paging with offset/limit. However, does not describe pagination behavior, rate limits, authentication needs, or what happens on empty results. Adequate but could be more detailed.

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 sentences: first states purpose concisely, second adds contextual details and paging advice. Front-loaded with critical information, no redundant words.

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 has 6 parameters, 4 required, and no schema descriptions, the description is incomplete. It explains the paging parameters (offset/limit) but omits explanation of dataset_id, edition, version, dimension. Leaves significant gaps for an agent to use correctly without additional knowledge.

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 coverage is 0%, but description only hints at limit/offset parameters for paging. Does not explain the required parameters (dataset_id, edition, version, dimension) or their semantics. The advice to page is helpful but insufficient to compensate for lack of parameter documentation.

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?

Clearly states verb 'List' and resource 'valid option codes for one dimension of a dataset version'. Distinguishes from siblings like get_dimensions (lists dimensions) and get_observations (uses option codes). No ambiguity.

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?

Provides context by explaining option codes are used for get_observations, implying when to use. Does not explicitly state when not to use or name alternatives, but the relationship to siblings is clear enough for differentiation.

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