gsc cluster queries

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

Annotations already cover read-only, idempotent, and non-destructive behavior honestly. The description adds meaningful algorithmic context beyond those annotations by stating that clustering relies on 'simple tokens and intent signals' rather than complex semantic analysis)Skip; this gives the agent a clearer model of what the tool will and will not do.

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 one sentence, front-loaded with the core action ('Cluster Search Console queries') and then lists the key clustering dimensions. Every part earns its place and there is no filler or repetition.

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?

The full input schema, annotations, and output schema carry a lot of the context, so the description does not need to be long. However, it leaves open how a user can influence the 'question', 'category', or 'topic' clusters and does not clarify whether the tool fetches data itself or operates on previously retrieved queries. For a tool with nine parameters and nested objects, a bit more operational context would improve completeness.

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?

The input schema has 100% description coverage, so the baseline is 3. The description does add conceptual meaning by grouping brand/non-brand, question, category, and topic signals, which loosely maps to brandTerms and categoryRules. However, it does not explain how those token types translate to specific parameters, and the schema already handles parameter-level semantics competently.

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 a specific verb and resource: clustering Search Console queries. It adds useful detail by listing the token types and intent signals used (brand/non-brand, question, category, topic). It does not explicitly differentiate from sibling tools like gsc_query_search_analytics, but the clustering action is distinct enough to be understood.

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 does not say when to use this tool versus alternatives such as gsc_query_search_analytics or gsc_validate_query. There is no explicit context about prerequisites, expected input flow, or when the clustering output is preferable to raw query data. Usage is only weakly implied by the verb 'cluster'.

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