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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is clear. The description adds pagination behavior (use of page_size and page_token), which is useful context beyond the annotations. However, it does not mention anything else like result ordering or potential consistency caveats. This is adequate but not rich, so a 3 is appropriate.

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 sentences long, front-loaded with the primary purpose, and every sentence adds value. There is no fluff or redundancy.

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 simple listing tool with pagination, the description covers what it does and how to paginate. An output schema exists, so return-value details are not needed. The tool name and description together make the scope unambiguous. This is complete for the complexity level.

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 input schema has 100% coverage, with each parameter already described. The description reiterates page_size and page_token but does not add new meaning beyond the schema details. Since the schema handles the heavy lifting, a baseline of 3 is warranted.

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 clearly states the tool's purpose with a specific verb and resource: 'List table ids in a BigQuery dataset.' This distinguishes it from siblings like execute_sql (running queries), get_table_info (detailed table metadata), and list_dataset_ids (dataset-level listing). The scope is unambiguous.

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 clear context for when to use the tool (to list table IDs in a dataset) and includes pagination instructions for use. It does not explicitly name alternatives or provide 'when not to use' exclusions, but the purpose statement and pagination guidance make the usage context clear.

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