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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint. The description adds important behavioral context: it is a direct ID-based lookup, not a search, and it returns citations and attribution. No contradiction with 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?

Four compact sentences with purpose first, output contents second, usage guidance third, and the non-search disclaimer last. Every sentence earns its place and no space is wasted on restating schema fields.

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?

Since no output schema exists, the description compensates by describing what returned evidence items contain, including citations and publisher attribution. The usage context is clear, though a tiny gap is that the phrase 'trend ID' is not explicitly mapped to the for_node_id parameter, leaving it to the schema to make that connection.

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 description coverage is 100%, so the schema fully documents each parameter. The description adds the conceptual framing of a trend-ID lookup, but does not repeat parameter-level details; this aligns with the baseline of 3.

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?

States a specific verb (Get), resource (supporting evidence behind a trend), and exactly what each item includes: source URL, location, brand names, publication date, category, and citation. The description clearly distinguishes the tool from search_graph with the 'direct lookup by trend ID — not a text search' note.

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?

Gives explicit timing: 'Use after search_graph when you need the supporting proof behind a trend.' It also explicitly excludes text-search usage and positions itself as a follow-up lookup. This leaves no ambiguity about when to select it over siblings.

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