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

Annotations already establish read-only, idempotent, non-destructive behavior, and the description adds meaningful context beyond that: default first-five-row sampling, pagination semantics, row-count comparison, and a caveat about header-looking rows requiring clarification. No annotation contradiction is present.

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 main retrieval behavior, then adds paging and data-caveat details without filler. It is dense but every sentence contributes useful operational context.

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 no output schema, the description usefully previews the returned metadata and rows, explains sampling and rowCount interpretation, and warns about header rows. It is nearly complete for this read tool, though the meanings of projectId and datasetId are left implicit.

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 schema already documents limit and offset with defaults and maximums, and the description reinforces their paging role. However, projectId and datasetId have no descriptions in either the schema or the description, so required-parameter semantics remain only partially covered at 50% schema coverage.

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 and resource: get one dataset, including its metadata shape and a window of rows. It also implicitly distinguishes this from list_datasets by specifying a single dataset and from mutation siblings by describing a read-style retrieval.

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?

It explains how to fetch more rows with offset and limit and warns about interpreting rowOffset against rowCount, but it does not explicitly say when to use this tool versus list_datasets, update_dataset, or other siblings. Usage is therefore clear but mostly implied.

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