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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds useful behavioral context: the data content, granularity by state and NAICS, and a concrete example with source. This goes beyond a simple read-only declaration, though it lacks details on pagination or response format.

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?

Three sentences, each earning its place: the first covers use cases, the second details return data, and the third provides an illustrative example and source. No filler or redundancy; information is front-loaded with the most important usage guidance.

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?

Without an output schema, the description fully explains return values by listing data points (counts, amounts, average sizes, top lenders, market share) and providing a concrete example with numbers. It also cites the data source, making it highly self-contained and complete for a data retrieval tool.

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 only 33% (year and state lack descriptions). The description compensates by indicating the tool filters 'by state and NAICS sector' and provides an example with specific values (Illinois, manufacturing, 2023), giving meaningful context to the parameters beyond the schema.

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 'Returns SBA 7(a) and 504 loan approval data' with specific metrics (counts, amounts, average sizes, top lenders, industry concentration). The verb 'Returns' is specific and the resource is well-defined, distinguishing it from sibling tools like CRA performance or FEC campaign finance.

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 opens with 'Use when assessing small business lending opportunity in a market, benchmarking a bank's SBA production against competitors, evaluating CRA lending performance by geography, or identifying industries with unmet capital needs.' This provides explicit, rich use-case guidance. However, it does not explicitly name alternative tools or state when not to use it, so it stops just short of the top score.

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