Keyword Cannibalization

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

Annotations already indicate readOnlyHint=true, openWorldHint=false, and destructiveHint=false. The description adds meaningful behavioral guidance beyond these: base analysis only on returned data, report exact numbers, avoid speculation, and explicitly say when data is insufficient. This aligns with openWorldHint=false and gives the agent concrete handling instructions.

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 well-structured: the first sentence defines the concept, the second states the output value, and the third provides essential analytical guardrails. Every sentence earns its place; there is no filler or repetition of schema details.

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?

With no output schema, the description partially conveys what the tool returns by stating it shows which pages rank for the same keywords and implies numeric results through 'report exact numbers.' It is sufficient for an agent to understand the tool's general output, though a more explicit return shape or field-level detail would improve completeness given the absence of an output schema.

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 83%, so the parameters are already well documented in the schema. The description adds no parameter-specific meaning beyond what the schema provides, such as date handling, row limits, or minImpressions. The baseline of 3 applies because the schema carries the parameter documentation burden.

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 detects keyword cannibalization and defines it as multiple pages from the same site competing for the same queries, splitting ranking potential. It identifies the output (which pages rank for the same keywords) but does not explicitly differentiate itself from sibling tools like search_analytics or topic_clusters, so it is clear but lacks explicit sibling positioning.

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?

Usage is implied: use when you need to detect keyword cannibalization or decide whether to consolidate pages. However, the description does not state when to prefer this tool over related tools such as find_opportunities or topic_clusters, nor does it provide exclusions or alternative routing. The IMPORTANT note is about data discipline, not about when to invoke the tool.

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