get_keyword_top_urls

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions what data is returned ('URLs with keyword count, estimated traffic, and Facebook shares') but lacks critical behavioral details: whether this is a read-only operation, if it requires authentication, rate limits, pagination behavior beyond parameters, or potential errors. For a tool with 6 parameters and no annotations, this is a significant gap in transparency.

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 concise and well-structured in two sentences: the first states the tool's purpose and selection criteria, and the second lists the returned data fields. Every sentence adds value without redundancy, making it easy to parse and understand quickly.

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 complexity (6 parameters, no annotations, no output schema), the description is moderately complete. It covers the tool's purpose and output fields but lacks behavioral context, usage guidelines, and detailed parameter explanations. For a data retrieval tool in a suite with many siblings, it should provide more guidance on when to use it and how results are structured, but it meets a basic threshold.

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 description adds minimal parameter semantics beyond the input schema, which has 100% coverage with detailed descriptions for all parameters. It implies the 'keyword' parameter is used for searching and mentions output fields ('keyword count, estimated traffic, Facebook shares') that relate to sorting options, but doesn't explain parameter interactions or provide examples. With high schema coverage, the baseline is 3, and the description doesn't add substantial value to elevate it.

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 website pages that rank for the largest amount of the analyzed keyword variations and have the highest traffic.' It specifies the verb ('returns'), resource ('website pages'), and criteria ('rank for keyword variations with highest traffic'). However, it doesn't explicitly differentiate from sibling tools like 'get_keyword_top' or 'get_keyword_full_top', which appear related but have unclear distinctions.

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 this tool versus alternatives. It doesn't mention prerequisites, such as needing a project or specific data setup, or compare it to siblings like 'get_keyword_top' or 'get_keyword_full_top'. The usage context is implied but not explicitly stated, leaving the agent to infer based on the tool name and description alone.

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