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

Annotations are already rich (readOnlyHint=true, openWorldHint=true), but the description goes beyond by adding 'deterministic', 'only counts the bounded request', and 'does not verify sources or infer causality'. It also usefully adds pricing context. These details clarify what the tool will and will not do, exceeding the annotation coverage.

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 entire description is two sentences: the first states purpose with examples, the second states limitations and pricing. No filler or redundancy; every phrase carries meaning. It is front-loaded and immediately informative.

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?

Despite no output schema, the output is understandably described as a 'two-dimensional count table', which is sufficient for this simple tool. The input constraints (bounded rows, at most 15 unique values) are covered in the schema, and the description clarifies the tool's limited scope. This is complete for a tool of this 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?

Schema description coverage is 100%, so parameters are already well documented. The description adds some illustrative context (e.g., 'event type by status or brand by review state') that aids understanding of rowDimension/columnDimension, but it does not introduce novel parameter semantics beyond the schema. This matches the baseline of 3.

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 opens with a specific verb and resource: 'Build a deterministic two-dimensional count table from buyer-supplied opaque rows.' It then gives concrete examples ('event type by status or brand by review state') which clarify the use case and distinguish it from sibling tools like metrics-aggregator or cooccurrence-analyzer. The scope is sharpened further with 'only counts the bounded request.'

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 implicitly tells when to use the tool: when a simple deterministic count table is needed from opaque rows. It also states exclusions ('does not verify sources or infer causality') and that it 'only counts the bounded request', which helps rule out inappropriate uses. However, it does not explicitly name alternative sibling tools, so it stops short of a 5.

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