gsc_build_cannibalization_decision_queue

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

No annotations are provided, so the description carries the full burden. It states the tool is 'read-only' and 'sampled,' and clarifies it is a 'diagnostic queue, not proof.' However, it does not disclose whether the queue is persistent, how sampling works, or potential side effects (e.g., if it overwrites previous queues). For a tool with no annotations, this is adequate but not comprehensive.

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, consisting of three short sentences. It is front-loaded with the core purpose. However, it could benefit from a more structured format (e.g., bullet points or explicit parameter guidance) given the complexity of the tool (8 parameters). As is, it is efficient but slightly under-structured.

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 complexity (8 parameters, output schema present but not described) and lack of schema descriptions, the description is incomplete. It does not explain how parameters affect the queue behavior, nor does it detail the output format. While the purpose is clear, the missing parameter semantics leaves significant gaps for an AI agent to correctly invoke the 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%, leaving 8 parameters completely undocumented. The description mentions 'dimensions query,page' and 'sampled' but does not connect these to any specific parameter like row_limit, max_queries, or min_total_impressions. The description adds no semantic value beyond the parameter names, failing to compensate for the lack of schema descriptions.

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 'Build a read-only sampled decision queue for likely keyword cannibalization,' specifying the verb, resource, and purpose. It distinguishes from siblings like gsc_build_content_action_queue by focusing on cannibalization. The line 'Uses one official Search Analytics query call with dimensions query,page' adds technical specificity, and 'diagnostic queue, not proof' clarifies limitations.

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 implies usage for diagnosing keyword cannibalization but does not provide explicit guidance on when to use this tool versus alternatives like gsc_build_content_action_queue. It lacks when-not-to-use conditions or prerequisites. The context of sibling 'build queue' tools suggests additional comparative guidance would be beneficial.

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