get_trends

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

With no annotations, the description carries the behavioral transparency burden and does a reasonable job: it specifies accepted timeframe formats, notes that omitting timeframe falls back to legacy data_mode defaults, and implies that timeframe overrides data_mode. This is concrete, useful behavioral context beyond the bare schema definitions.

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 compact and front-loaded with the main purpose, then devotes one focused paragraph to the most nuanced parameters. Every sentence earns its place, with no filler or redundant restatements of the schema.

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 tool has a complete input schema, an output schema, and only one required parameter. The description covers the important edge case around timeframe omission and legacy defaults, making the tool adequately callable. The main gap is sibling-selection guidance, but that is largely captured by the usage dimension.

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 description coverage is 100%, so the baseline is 3. The description adds value by giving concrete examples of valid timeframe values and explaining the legacy default behavior for data_mode when timeframe is omitted, going beyond the schema descriptions.

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 action and resource: pull search interest over time for keywords. It is specific enough to distinguish from most sibling tools, but it does not explicitly differentiate against related tools like get_interest_by_region or get_growth, so it falls just short of full sibling differentiation.

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 provides no guidance on when to use get_trends versus its many siblings. It discusses timeframe and data_mode parameter behavior, but that is parameter-level guidance, not tool-selection guidance, so an agent is left without explicit context for choosing this tool over alternatives.

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