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

With no annotations provided, the description fully discloses behavioral traits: it reveals a known bug regarding awards over $10M and clarifies that statistics are about case records, not population rates. This adds significant value beyond the schema and annotations.

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 concise and well-structured: it starts with the core purpose, then lists key parameters and return fields, followed by a bug disclosure and dataset framing. Every sentence adds information with no wasted words.

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?

Given the complexity of an aggregation tool with five filters and no output schema, the description covers the essential return fields and a notable bug. However, it does not explain the default grouping or how each filter works, and the output structure is implied rather than explicit.

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. It explains the 'group_by' parameter and its options, but does not describe the other four parameters (vaccine, is_death, pediatric_only, condition_category). Their names are somewhat self-explanatory, but the lack of elaboration means the description fails to fully compensate.

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 the tool's function: 'Aggregate statistics over the case corpus, optionally filtered.' It lists specific grouping options and return fields, distinguishing it from sibling tools that fetch individual records or search.

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 usage for aggregations ('Aggregate statistics') and provides context about the dataset ('VICP case-record dataset'). However, it does not explicitly compare to alternatives or state when not to use it, leaving room for ambiguity among the many sibling tools.

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