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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is well covered. The description adds that it searches identifiers, names, and descriptions — useful scoping detail beyond the annotations, though it doesn't disclose result limits, ranking behavior, or match semantics.

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?

A single concise sentence that efficiently conveys what is searched and in what form. No wasted words, no redundancy with the schema or annotations.

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?

With a single well-documented parameter, an output schema present, and read-only annotations, the tool is simple enough that the description is adequate. It doesn't disclose result-count limits or match behavior, but given the tool's simplicity, the completeness is satisfactory.

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 single parameter 'query' has 100% schema description coverage ('Plain words that describe the required financial data'), and the description reinforces this by specifying it should be a plain-language financial-data query, adding the financial-data domain constraint beyond the schema's generic phrasing.

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 states a clear verb ('Search') and resource ('dataset identifiers, names, and descriptions') with a plain-language query approach. It doesn't explicitly distinguish from datasets_list/datasets_describe, though the free-text 'search' nature is implied and differentiates from list/describe siblings.

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 conveys it accepts plain-language financial-data queries, implying use for discovery. It doesn't explicitly state when to use it versus datasets_list (enumerate) or datasets_describe (inspect one), leaving the alternative-selection guidance implicit rather than explicit.

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