gsc_intent_breakdown

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

With no annotations, the description carries the full burden and discloses substantial behavioral constraints: base analysis only on data returned, avoid speculation, admit insufficient information, and present as a rich visual artifact. This goes beyond the schema and gives clear execution boundaries, though data-source limitations or performance characteristics are not mentioned.

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 front-loaded with the purpose and then organized into clearly labeled 'IMPORTANT' and 'PRESENTATION' sections. While longer than the two-sentence ideal, each section carries distinct and necessary instructions (honesty rules and visualization requirements) that justify the length.

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?

There is no output schema, so the description compensates by specifying the key output metrics (clicks, impressions, CTR by intent category) and the expected artifact-based presentation. It is reasonably complete for a read-only analytics tool, though it does not define the exact regex patterns or edge-case handling.

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%, with both 'days' and 'dataset' already described in the input schema. The tool description adds no additional parameter-level detail, so the baseline score of 3 is appropriate.

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 identifies the specific operation ('Classify all your ranking queries by search intent') and the output metrics ('clicks, impressions, and CTR by intent category'), distinguishing this tool from sibling GSC analysis tools. The verb 'Classify' and resource 'ranking queries' are explicit.

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 clear context for when to use the tool (when intent categorization of queries is needed), but it does not explicitly name alternatives or state when not to use it. The 'IMPORTANT' and 'PRESENTATION' sections add further usage expectations around data honesty and output format.

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