Interest over time

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

With no annotations, the description carries the full transparency burden. It discloses a key behavioral detail: values are normalized on a 0-100 scale and are not absolute search volume, which prevents misinterpretation. It also conveys the comparative behavior when multiple keywords are used. It does not mention any side effects or permissions, but for a read-only data retrieval tool this is acceptable. Some specifics like aggregation window or time-series granularity are omitted, hence a 4 rather than 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?

The description is two sentences, tightly packed with purpose, usage, and a critical interpretative note. There is no fluff or redundancy; every word contributes to understanding. The structure is logical: function, then when to use, then key behavior. This is exemplary conciseness.

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?

Although there is no output schema, the description provides enough context about the return value ('normalized relative interest (0-100)') and its comparative nature to manage expectations. It also includes usage context that helps an agent decide between siblings, covering the 'when to use' aspect. The tool is simple (3 parameters, no nested objects), and the description addresses all necessary dimensions for effective selection and invocation.

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 coverage is 100% with descriptions for all parameters, and the tool description adds extra meaning beyond the schema. It explains that keywords can accept topic IDs from search_topics and that multiple keywords are compared against each other. It also clarifies that an empty region string means worldwide. This rich contextualization makes parameter usage clearer than the schema alone.

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 specifies the function: 'Get relative search interest for one or more terms over a historical period.' It explicitly differentiates the tool from siblings by emphasizing the time-series aspect and the comparative use case with multiple keywords ('whether it is rising or falling, or how several things compare'). This makes the tool's purpose unambiguous and distinct from region, related queries, or trending tools.

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 gives explicit usage triggers: 'Use this when the user asks how popular something is, whether it is rising or falling, or how several things compare.' It also clarifies that passing multiple keywords compares them on one scale and that values are relative (0-100), not absolute search volume. This provides direct guidance on when and how to invoke the tool, though it does not explicitly state when to prefer alternatives, the positive triggers are strong enough.

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