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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable context beyond that: 'Data reflects actual filed returns, not survey estimates' and 'Source: IRS Statistics of Income Division', which gives provenance and reliability without contradicting the 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 front-loaded with use cases and a clear statement of what it returns. The example is illustrative but makes the description longer than strictly necessary; every sentence adds value, so it is not overly verbose.

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 tool's simplicity (2 params, no output schema), the description covers use cases, data source, output fields (gross receipts, net income margins, effective tax rates), and provides a concrete example. It is complete enough for an agent to select and invoke the tool correctly.

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 coverage is 50%; the industry parameter is already described in the schema, and the description reinforces it with an example ('Healthcare and Social Assistance'). However, the entity_type parameter is not explained in the description and only has an enum/default in the schema, so the description does not fully compensate for the missing schema description.

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 a specific verb+resource: 'Returns IRS SOI aggregate statistics from actual filed corporation income tax returns' along with the key metrics (gross receipts, net income margins, effective tax rates). This distinguishes it from sibling tools that focus on spend benchmarks, market signals, or other data sources.

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 opening 'Use when benchmarking financial performance..., establishing valuation comparables..., assessing typical effective tax rates..., or producing financial due diligence context' provides explicit use cases. However, it does not name alternative tools or state when NOT to use this tool, so it lacks the exclusion/alternative guidance that would merit a 5.

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