Aggregate cataloged data

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

With no annotations provided, the description must fully disclose behavioral traits. It only states that it is declarative and constrained, but does not explain return behavior, side effects, read-only nature, or edge cases. This is a significant transparency gap for a tool with no output schema or annotation support.

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 extremely concise, containing only two short sentences. It front-loads the core purpose ('Declarative aggregation over one cataloged dataset') and appends relevant constraints. Every word earns its place with no wasted content.

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?

The tool is complex: 9 parameters, nested filter objects, several enums, no output schema, and no annotations. The description provides almost no context beyond a one-line summary, leaving the agent without crucial behavioral or semantic details. It is inadequate for safe and correct invocation.

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 0%, so the description must compensate for explaining the 9 parameters. It only clarifies that the dataset is a cataloged dataset and that expressions are limited, which vaguely relates to the 'dataset' and 'metrics' parameters. It provides no meaning for filters, date ranges, dimensions, timeBucket, limit, or orderBy.

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 identifies the tool's function: declarative aggregation over a single cataloged dataset. It is specific with the verb 'aggregate' and the resource 'cataloged dataset', and the constraints 'No joins, arbitrary expressions, or file paths' further distinguish it from potential sibling tools.

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 implies when to use the tool: when you need declarative aggregation over exactly one cataloged dataset. It also provides exclusions ('No joins, arbitrary expressions, or file paths'), which informs users about non-intended use cases. However, it does not explicitly name alternative tools or provide detailed when/when-not guidance.

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