get_url_keywords

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: it's a read operation (implied by 'returns'), includes comprehensive data insights, supports filtering, and discloses the API cost ('1 credit per result row returned'). It also notes the ranking scope for Google vs. Bing. While it doesn't cover all potential behaviors like error handling or pagination details, it provides substantial context beyond basic functionality.

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 efficiently structured in three sentences: the core purpose, the data returned, and usage/cost details. Every sentence adds value without redundancy. It's front-loaded with the main function and appropriately sized for the tool's complexity.

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 the tool's moderate complexity (7 parameters, nested objects) and lack of annotations or output schema, the description does well by covering purpose, data insights, filtering, and cost. However, it doesn't detail the response format or pagination behavior, which would be helpful for an agent to interpret results. It's largely complete but has minor gaps in output expectations.

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 schema already documents all parameters thoroughly. The description adds some value by mentioning filters ('position range, search volume, difficulty, or keyword patterns') and the API cost implication, but it doesn't provide additional parameter semantics beyond what's in the schema descriptions. This meets the baseline for high schema coverage.

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's purpose: 'Returns a list of keywords for which the specified URL ranks in top-100 Google search results.' It specifies the verb ('returns'), resource ('keywords'), and scope ('top-100 Google search results'), distinguishing it from sibling tools like get_domain_keywords or get_keywords_info which have different scopes.

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 clear context for when to use this tool: analyzing a specific URL's keyword rankings. It mentions 'Use filters to narrow down by position range, search volume, difficulty, or keyword patterns,' which gives practical guidance. However, it does not explicitly state when not to use it or name alternative tools for different use cases.

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