interest_over_time

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

With no annotations, the description carries the full behavioral burden, and it does a solid job: it discloses the 0-100 scale, downsampling to ~60 points, the summary fields, and valid gprop values. It does not mention error behavior or rate limits, but it provides meaningful operational detail beyond a bare verb phrase.

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 core output and keyword constraint stated first. The gprop list is efficient, and the parenthetical rationale for youtube adds useful context without excessive verbosity.

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 an output schema exists, the return value shape is handled externally. However, the description lacks guidance on geo/category semantics and does not explain valid timeframe formats beyond the default, leaving some ambiguity for an agent making a correct call.

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 0%, so the description must compensate for parameter meaning. It explains the gprop choices and limits keywords to 1-5, but it does not clarify geo, category, or timeframe formats beyond schema defaults, leaving part of the parameter surface undocumented.

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 returns search-interest time series with per-keyword summary metrics, which conveys the core function of a time-series tool. It is distinct enough from siblings like interest_by_region and related_queries by emphasizing the temporal dimension, though it does not explicitly name those alternatives.

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?

There is no explicit guidance on when to use this tool versus alternatives such as compare_keywords, interest_by_region, or trending_now. The time-series nature is implied, but no exclusions, prerequisites, or routing advice are provided, leaving the agent to infer the appropriate context.

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