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

Annotations already establish the safety profile (readOnlyHint, idempotentHint, destructiveHint=false), so the bar is lower. The description adds useful capability context beyond them: simple filters, ordering, paging, and the fact that the response includes the total row count.

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?

Two sentences, front-loaded with the verb and resource, with no redundant restatement of the title or schema. Every clause adds information about capability or output.

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?

Read-only tool with full parameter documentation, complete annotations, and no output schema; the description compensates by noting the total row count in the response. Nothing essential for correct invocation is missing.

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%, so every parameter (limit, where, offset, order_by, descending, dataset) is already documented with defaults and operator syntax. The description only gestures at 'simple filters, ordering and paging' without adding syntax or format detail beyond the schema, so the baseline of 3 applies.

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?

States a specific verb and resource ('Reads rows from a dataset') and adds the intent ('inspect or analyse what is stored') with a concrete example. This clearly separates it from write-oriented siblings like upsert_rows and delete_rows, though it never names an alternative explicitly.

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?

Provides a clear usage context in the parenthetical example ('to see the latest month before adding the next one'), which tells the agent when this read tool is appropriate. It lacks any explicit when-not guidance or routing to sibling tools such as get_view or check_view.

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