gsc_search_analytics

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 discloses key behaviors: it is a read-only query tool, it returns a single totals row when dimensions is empty, it supports paging via start_row, and it has a row_limit cap of 25000. It does not describe the output format, but an output schema exists, so that burden is partially lifted. The description adds meaningful behavioral context beyond the schema.

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 usage guidance, then uses a compact Args block for parameters. It is appropriately sized for a 9-parameter flexible tool and every line earns its place. It loses one point because the Args block is a bit dense and could be slightly more scannable, but it is still well-structured and efficient.

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 highly flexible 9-parameter tool with no annotations and 0% schema coverage, the description covers all parameters, defaults, valid values, paging, and the relationship to sibling tools. An output schema exists, so return-value documentation is not required. The description is complete enough for an agent to select and invoke this tool correctly.

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 compensate, and it does thoroughly. Every parameter is explained with concrete semantics: site_url must match list_sites output, dimensions lists valid values and the empty-list behavior, dates use YYYY-MM-DD with the omit-both-to-use-days rule, days has a default, row_limit has a max, search_type enumerates valid values, filters explains the operator list, and start_row is for paging. This is exemplary parameter documentation.

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 states a specific verb ('Run'), a clear resource ('Search Console performance query'), and explicitly positions it as the most flexible read tool for anything the shortcut tools do not cover. It distinguishes itself from the many gsc_* sibling tools by framing itself as the general-purpose fallback, which is exactly the kind of differentiation an agent needs.

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 says 'use it for anything the shortcut tools do not cover,' which gives a clear when-to-use signal relative to the gsc_* siblings. It does not explicitly list which shortcut tools exist or enumerate exclusions, but the context signals show many gsc_* siblings, and the phrase 'shortcut tools' implies those are the alternatives. This is clear context without exhaustive exclusions.

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