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

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description adds useful behavioral context by naming the direct-lookup-by-ID nature, the non-search semantics, and enumerating the fields returned for each evidence item, which goes beyond the annotation information.

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 first sentence says what the tool returns, the second pinpoints when to use it, and the third clarifies what it is not. There is no filler; each sentence earns its place and the information is front-loaded.

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 there is no output schema, the description compensates by explicitly describing the shape of returned evidence: source URL, location, brand names, publication date, category, and formatted citation. It also connects to the prior search step and warns about direct ID lookup, covering the key operational context an agent needs.

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%, with all four parameters described in the schema, including detailed guidance and examples for graphId and the warning on for_node_id. The description itself adds only marginal semantic reinforcement ('direct lookup by trend ID'), so the schema already carries the parameter-documentation burden.

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 retrieves source articles, case studies, and statistics behind a specific trend, which establishes the verb, resource, and outcome. It also explicitly distinguishes itself from a text search tool, so an agent can differentiate it from search_graph and other 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?

It gives explicit guidance: use after search_graph when supporting proof behind a trend is needed, and it clarifies the inverse ('not a text search tool'). This answers when to use it and contrasts it with the most likely alternative without ambiguity.

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