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

The annotations already declare this as a safe, read-only, idempotent, closed-world operation, so the bar is lower. The description adds useful data-granularity context by clarifying that referring-domain and page totals are aggregates rather than individual links, but it does not discuss pagination, authentication, or other behavioral traits.

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 two short, front-loaded sentences with very little waste. The first identifies the returned resource, and the second immediately adds the aggregate caveat, so it is concise and well-structured despite being slightly fragmentary.

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?

With six parameters, only 17% schema description coverage, and no output schema, the definition should explain parameter behavior and return shape more fully. It gives only a high-level content note and omits pagination, sorting, limiting, and required identifier semantics.

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 only 17%, and the description provides no meaning for project_id, dataset_id, sort, limit, direction, or cursor. It fails to compensate for the low schema coverage, leaving parameter usage almost entirely undocumented.

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 that the tool returns rows of a keyword or backlink dataset, which identifies the specific resource and output shape. It is clear, but it does not explicitly distinguish this tool from related read_search_* or read_query_evidence siblings, so it falls short of a 5.

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?

There is no guidance on when to use this tool versus alternatives, prerequisites, or which dataset types are appropriate in which situations. The description only states what is returned, leaving usage entirely implied.

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