List tables and views

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered by structured data. The description adds nothing beyond that — no note on whether results are paginated, cached, or scoped by permissions, which for a BigQuery metadata call would be genuine added value.

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?

A single sentence with zero filler, front-loaded with the verb and the scoped resource. Nothing to trim and nothing essential buried.

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 trivial read-only listing tool with two fully documented parameters and annotations covering safety, the description is nearly sufficient. The only minor gap is that no output schema exists, so the return shape (table names, view flags, row counts) is unstated.

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%: dataset_id carries a concrete example and project_id documents its config-default behavior. The description adds no parameter meaning beyond the schema, so the baseline 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?

Clear verb+resource: 'List the tables and views' names both the operation and the object, and the scope 'of a BigQuery dataset' separates it from list_datasets (project-level) and describe_table (single-table detail). It stops short of explicitly naming those siblings, so it is clear but not fully disambiguating on its own.

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 gives no when-to-use guidance, no prerequisites, and no mention of alternatives such as list_datasets or describe_table. Usage is only implied by the listing verb, leaving the agent to infer the call context.

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