safe_query

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

With no annotations, the description covers safety restrictions and auto-limit. However, it omits details about return format, error handling, and performance impacts, leaving some behavioral aspects unclear.

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 tightly written with a clear purpose upfront, followed by safety details and a concise parameter list. Every sentence contributes essential information without 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 query tool with 3 parameters and an output schema, the description covers safety, usage, and parameters. It does not explain return values, but the output schema likely fills that gap. Overall adequate for the tool's complexity.

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?

Despite 0% schema description coverage, the description explains each parameter in plain language: query_id for context, sql with an example, and limit with a cap. This fully compensates for the schema's lack of descriptions.

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 it executes a SELECT-only SQL query against a dataset table, distinguishing it from sibling tools like describe_data_query or get_metric_summary by specifying the exact operation and scope.

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 explicitly lists blocked keywords and auto-applied LIMIT, giving clear constraints. While it does not directly compare to alternatives, the context of blocked operations provides implicit guidance for when to use this tool.

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