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

Annotations already establish that this is a safe, read-only, closed-world search. The description adds useful behavioral context beyond annotations: it says results include hours in stock, price per hour, scenario fit, requirement coverage, and custom options when stock does not fit. Pagination or result limits are not mentioned, keeping it from a 5.

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, front-loaded with the search action and catalog scope, then the example and return-value summary. Every element earns its place without repetition.

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?

For a simple one-parameter search tool with annotations covering safety and no output schema, the description supplies enough context: what to query, what the response contains, and what happens when nothing matches. An agent has what it needs to invoke it correctly.

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?

With one parameter and 100% schema description coverage, the schema already documents the query dimensions. The description adds meaning by emphasizing that the query should be a plain-English need and gives a concrete example, which helps an agent formulate the input correctly.

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 uses a specific verb ("Search") and resource ("datasets") and scopes it to a licensable data catalog with concrete examples. It is clearly distinguishable from sibling tools like get_dataset or request_quote, which imply detail retrieval and quoting rather than discovery search.

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?

It clearly indicates when to use the tool: when you have a plain-English data need and want matching inventory plus custom-collection fallback. It does not explicitly name when to move to siblings such as get_dataset or get_pricing_and_terms, so it falls short of full when/when-not routing.

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