run_query_with_validation

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

With no annotations, the description carries the full behavioral burden. It usefully discloses that validation fails for queries over 1 TB or containing DML, but it omits authentication needs, billing implications, whether the query actually executes after validation, and what the response looks like.

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 a single front-loaded sentence with no wasted words. The core action and validation constraints are stated immediately.

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 three-parameter tool with a fully described schema, the description covers the main execution and validation behavior. However, it does not explain return values despite there being no output schema, and it does not mention the closely related dry_run_query sibling.

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 all three parameters are documented in the schema. The description does not add meaning beyond the schema for query, projectId, or maxResults, making the baseline 3 appropriate.

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: it runs a BigQuery query and performs dry-run validation. It clearly defines the validation scope, including failure thresholds for size and DML, but it does not explicitly distinguish this tool from the sibling dry_run_query.

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 constraints such as the 1 TB limit and DML rejection, which imply this is for safe SELECT execution. However, it provides no explicit guidance on when to use this tool versus dry_run_query, nor does it explain when not to use it.

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