query_datasets

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

With no annotations provided, the description carries full responsibility. It discloses key behavioral traits: the unreliability of $search, the effect of exclude_discontinued, and the return type. It could additionally mention that this is a read-only operation, but the search/query phrasing implies non-destructive behavior.

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 well-structured with clear sections: purpose, recommendation, args, and returns. It is somewhat lengthy due to the example and detailed parameter notes, but every sentence adds value. The front-loaded first line immediately communicates what the tool does.

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 comprehensive for a tool with 10 parameters and an output schema. It explains the purpose, parameter semantics, a critical behavioral caveat (unreliable $search), and return type. It leaves no major gaps for the agent to guess.

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 zero descriptions, so the description fully compensates. Every one of the 10 parameters is explained with meaningful context (e.g., 'filter: OData $filter -- use contains() for title search', 'exclude_discontinued: Prepend a default filter'). This goes far beyond restating parameter names.

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 the tool's purpose: 'Search datasets with OData filtering, sorting, and pagination.' This uses a specific verb ('search') and resource ('datasets'), and distinguishes it from sibling tools like get_observations or get_metadata, which serve different functions.

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 strong guidance on parameter usage, explicitly recommending to use 'filter' with contains() instead of 'search', and explaining why search is unreliable. It does not explicitly compare against sibling tools, but the context makes it clear this is for querying datasets, which is sufficient for most cases.

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