find_keyword_cannibalization

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds value beyond that by disclosing what the response contains (a primary page recommendation and a fix) and by explaining the threshold semantics behind the filters.

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 purpose sentence is front-loaded and the Args block is terse with one line per parameter, each earning its place. The Python-docstring framing is slightly mechanical but adds no filler.

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 an output schema present, return values need not be explained, and every input is documented. What remains missing is context around data scope or limitations (e.g. property/date-range constraints, cost of a wide days window), which would round out a moderately complex analytical tool.

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 carry the burden – and it does: all five parameters are documented with meaning and defaults, including the fallback for site_url (GSC_SITE_URL) and the precise interpretation of min_share as a share of a query's impressions. This is exactly the compensation the schema gap requires.

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 first sentence names a specific verb ('Find') and a precise analytical resource ('queries where two or more of your pages compete') and states what the result contains (suggested primary page + fix). This is clearly distinguishable from sibling diagnostics such as find_striking_distance_keywords and find_low_ctr_opportunities.

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 by the purpose statement – an agent can infer this is for diagnosing internal keyword overlap – but there is no explicit when-to-use, when-not-to-use, or named alternative among the many sibling analytics tools. Nothing is misleading, but the routing guidance is left to inference.

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