Validate a BigQuery SQL query and estimate the bytes it will process before running it, so you can catch errors and control query cost.
Perform a dry run of a BigQuery query to check if it's valid and estimate its size
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The SQL query to dry run | |
| projectId | No | Google Cloud project ID (optional, uses default if not provided) |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It does disclose the key behavioral trait that the query is not actually executed (dry run) and that a size estimate is returned, which is meaningful. It omits permissions requirements, cost implications, and how errors are surfaced.
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 efficient sentence with the action and both outcomes front-loaded; nothing is redundant. It is arguably too sparse rather than wasteful, which keeps it just shy of 5.
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 and no annotations, the description should describe the shape of the result (validation errors vs. bytes-processed estimate, schema preview). It only gestures at 'estimate its size', leaving the return value under-specified for an agent that must interpret the dry-run result.
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 both parameters are already documented ('query', 'projectId' with default behavior). The description adds no syntax, format, or dialect detail beyond the schema, so 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?
States a specific verb+resource ('dry run of a BigQuery query') and names both outcomes: validity check and size estimate. It implicitly contrasts with the only sibling, run_query_with_validation, by being the non-executing variant, but never names the sibling 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?
The phrase 'to check if it's valid' hints at the pre-flight validation use case, which is the correct context for choosing this over run_query_with_validation. However, there is no explicit when-to-use/when-not guidance, no mention that this avoids execution cost, and no named alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.