get_search_query_performance

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

With no annotations provided, the description carries the transparency burden. It discloses that the local instance is a stub, which is critical behavior. However, it omits details about authentication, rate limits, error behavior, or the fact that it is a read-only operation (though implied by '[read]').

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 only two sentences, front-loaded with the core purpose and critical caveat. Every word earns its place, with no redundancy.

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?

For a tool with 7 parameters and no output schema, the description covers purpose and a key behavioral constraint (stub). However, it lacks description of return values, error handling, or guidance on common use cases, leaving some gaps.

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%; all 7 parameters have adequate descriptions. The description adds no extra meaning beyond 'market share and conversion data', so it meets the baseline for high coverage without adding value.

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 'Market share and conversion data' for search queries, using a verb-resource structure ('read'). It distinguishes from sibling 'get_' tools by specifying the data type, and the prefix '[Ads / read]' clarifies domain and action.

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 notes the tool is 'Hosted endpoint only; this local stdio server is an introspection stub', implying it should only be used via the hosted endpoint. However, it does not explicitly guide when to use this tool over siblings like get_campaign_performance or get_keyword_performance.

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