blv_get_dataset_info

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

Annotations already declare readOnly, idempotent, and openWorld hints, so the description doesn't need to restate safety. It adds value by describing the output content (metadata, URLs, formats, license) and the relationship to another tool, providing context beyond 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 two sentences, front-loaded with the core purpose, and no extraneous text. Every sentence adds value.

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 existence of an output schema (so return values are documented), the description is complete: it covers what the tool does, when to use it, and the key input. No gaps remain.

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 100%, and the schema already describes the parameter as 'CKAN dataset name/slug (from blv_list_datasets).' The description reiterates this without adding new semantic detail, so baseline 3 is appropriate.

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 it provides 'detailed metadata and resource URLs' for a BLV dataset, using a specific verb (retrieve) and resource (dataset info). It distinguishes itself from sibling tools that focus on specific data types by mentioning it is for general dataset info, and explicitly ties to blv_list_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?

The description gives a clear use case: obtain download URLs and formats after finding a dataset via blv_list_datasets. While it doesn't explicitly state when not to use it, the sibling context and the mention of the prerequisite tool provide adequate guidance.

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